News
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May 20, 2013
Title: New Tool for Visualizing High-Dimensional Single-Cell Data Reveals Phenotypic Heterogeneity in Leukemia
Researchers in the Columbia Initiative in Systems Biology have developed a computational method that enables scientists to visualize and interpret high-dimensional data produced by single-cell measurement technologies such as mass cytometry. The method, called viSNE (visual interactive Stochastic Neighbor Embedding), has just been published in the online edition of Nature Biotechnology. It has particular relevance to cancer research and therapeutics. As Columbia University Medical Center reports:
Researchers now understand that cancer within an individual can harbor subpopulations of cells with different molecular characteristics. Groups of cells may behave differently from one another, including in how they respond to treatment. The ability to study single cells, as well as to identify and characterize subpopulations of cancerous cells within an individual, could lead to more precise methods of diagnosis and treatment.
“Our method not only will allow scientists to explore the heterogeneity of cancer cells and to characterize drug-resistant cancer cells, but also will allow physicians to track tumor progression, identify drug-resistant cancer cells, and detect minute quantities of cancer cells that increase the risk of relapse,” said co-senior author Dana Pe’er, associate professor of biological sciences and systems biology at Columbia. The other co-senior author is Garry P. Nolan, professor of microbiology & immunology at Stanford. [...]
The viSNE software can analyze measurements of dozens of molecular markers. In the maps that result, the distance between points represents the degree of similarity between single cells. The maps can reveal clearly defined groups of cells with distinct behaviors (e.g., drug resistance) even if they are only a tiny fraction of the total population. This should enable the design of ways to physically isolate and study these cell subpopulations in the laboratory.
Although the algorithm underlying the method is complex, Dr. Pe’er expects that all researchers, no matter their level of mathematical expertise, will be able to use viSNE.
To demonstrate the software’s utility, Dr. Pe’er and her colleagues used mass cytometry and viSNE to study bone marrow cells from patients with acute myeloid leukemia. Currently, clinicians can incorporate at most 4 to 8 markers to assess the cells. Because mass cytometry and viSNE can incorporate many more markers, viSNE is able to identify more subtle differences between cells. Using the algorithm, Dr. Pe’er and her colleagues were able to reveal previously unrecognized heterogeneity in the bone marrow cells they studied.
The researchers also showed that viSNE could detect minimal residual disease (MRD) — extremely small quantities of cancer cells that persist after chemotherapy and raise the risk of recurrence. “In blinded tests, we were able to find as few as 20 cancer cells out of tens of thousands of healthy cells,” said Dr. Pe’er. Such a small quantity of cells is extremely difficult to detect, even by the most experienced pathologist.
“The ability to detect MRD is critical for curing cancer,” added Dr. Pe’er. “Eliminating even 99.9 percent of a tumor doesn’t bring about a cure. You have to be able to find, and then eliminate, the tiny populations of cells that can survive therapy and lead to disease relapse.”
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April 22, 2013
Title: Study of Cancer Metabolism Identifies Potential Drug Targets to Starve Tumors
A large study analyzing gene expression data from 22 cancer types has identified a broad spectrum of metabolic expression changes associated with cancer. The analysis, led by Dennis Vitkup, first author Jie Hu, a postdoctoral research scientist in the Vitkup lab, with a multi-institutional group of collaborators, also identified hundreds of potential drug targets that could cut off a tumor’s fuel supply or interfere with its ability to synthesize essential elements necessary for tumor growth. The study has just been published in the online edition of Nature Biotechnology.
As Columbia University Medical Center reports:
The results should ramp up research into drugs that interfere with cancer metabolism, a field that dominated cancer research in the early 20th century and has recently undergone a renaissance.
“The importance of this new study is its scope,” says Dennis Vitkup, PhD, associate professor of systems biology and biomedical informatics at CUMC, and the study’s lead investigator. “So far, people have focused mainly on a few genes involved in major metabolic processes. Our study provides a comprehensive, global view of diverse metabolic alterations at the level of gene expression.” […]
Notably, the researchers found that the tumor-induced expression changes are significantly different across diverse tumors. Although some metabolic changes—such as an increase in nucleotide biosynthesis and glycolysis—appear to be more frequent across tumors, others, such as changes in oxidation phosphorylation, are heterogeneous. […]
For cancer researchers looking for new drug targets, Vitkup’s team also found hundreds of differences between normal cells’ and cancer cells’ use of isoenzymes. This opens up additional possibilities for turning off cancer’s fuel and supply lines… “Inhibiting specific isoenzymes in tumors may be a way to selectively hit cancer cells without affecting normal cells, which could get by with other isoenzymes,” Hu says. […]
Targeting metabolism may be a way to strike cancer at its roots. “Cancer cells usually have multiple ways to turn on their growth program,” Vitkup says. “You can knock out one, but the cells will usually find another pathway to turn on proliferation. Targeting metabolism may be more powerful, because if you starve a cell of energy or materials, it has nowhere to go.”
For more information, read the complete news feature at Columbia University Medical Center.
April 17, 2013
Title: Columbia University Team Named Best Performer in DREAM Breast Cancer Challenge
The team of Professor Dimitris Anastassiou and graduate students Wei-Yi Cheng and Tai-Hsien Ou Yang has been recognized as the best performer in the Sage Bionetworks – DREAM Breast Cancer Prognosis Challenge. This challenge, one of four organized as part of the seventh Dialogue for Reverse Engineering Assessments and Methods (DREAM7), was designed to assess the ability of participants’ computational models to predict breast cancer survival using patient clinical information and molecular profiling data. As a reward for this accomplishment, the journal Science Translational Medicine has just published a paper from the Anastassiou lab describing their model.
The Columbia University researchers based their DREAM entry on previous work to identify what they call attractor metagenes, sets of strongly co-expressed genes that they have found to be present with very little variation in many cancer types. Moreover, these metagenes appear to be associated with specific attributes of cancer including chromosomal instability, epithelial-mesenchymal transition, and a lymphocyte-specific immune response. As Wei-Yi Cheng comments in Sage Synapse, “We like to think of these three main attractor metagenes as representing three key ‘bioinformatic hallmarks of cancer,’ reflecting the ability of cancer cells to divide uncontrollably and invade surrounding tissues, and the ability of the organism to recruit a particular type of immune response to fight the disease.”
In the first stage of the DREAM challenge, participants were asked to train their algorithms on METABRIC, a collection of genomic and clinical data generated from approximately 2,000 breast cancer samples. The Anastassiou team found that searching for attractor metagenes in the data enabled them to make strong prognoses under certain conditions. They then developed a computational model that combined these gene signatures. In the final stage of the Challenge, the accuracy of each of the participants’ models was tested against data from a new set of 184 breast cancer patients, generated for the Challenge with the support of a donation by the Avon Foundation. The Columbia team was the best performer in all stages of the Challenge, including the final validation exercise, where they correctly predicted which of two patients would survive longer in 76% of cases, an exceptionally high performance. Approximately 350 participants from 35 countries registered for the Challenge.
Anastassiou and his teammates see this achievement as an important validation of their model, particularly because it uses features (the attractor metagenes) which they had independently discovered to be present in multiple cancers before they entered the Challenge, without considering any association with prognosis. “If these universal signatures of cancer are prognostic in breast cancer, then why not in other types of cancer? And if they are useful for prognosis, why not for predicting drug response as well?” remarks Anastassiou. He and his students now hope that their characterization of attractor metagenes could lead to the development of universal biomarkers that could ultimately help to improve diagnosis and treatment for many different cancer types.
In addition to the Anastassiou lab's paper, Science Translational Medicine has published a report on the Challenge by the organizers.
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March 18, 2013
Title: Harris Wang Joins Columbia Initiative in Systems Biology
Harris Wang has joined Columbia University Medical Center as an Assistant Professor in the Columbia Initiative in Systems Biology and the Department of Pathology and Cell Biology. His research focuses on understanding the evolution of the ecosystems that develop within heterogeneous microbial communities. Using approaches from genome engineering, DNA synthesis, and next-generation sequencing, he studies how genomes in microbial populations form, maintain themselves, and change over time, both within and across microbial communities. His goal is to use synthetic biology approaches to engineer ecologies of microbial populations, such as those found in the gut and elsewhere in the human body, in ways that could improve human health.
Dr. Wang earned his BS in physics and applied mathematics at the Massachusetts Institute of Technology. He completed his PhD in biophysics at Harvard University, where, as a graduate student in George Church’s laboratory, he developed a technique called Multiplex Automated Genome Engineering (MAGE). This approach made it possible to produce synthetic organisms with novel properties, and to accelerate the process of directed evolution of gene networks and genomes. Most recently, he was a Wyss Technology Development Fellow and member of the Department of Systems Biology at Harvard University.
Dr. Wang has been recognized as a National Science Foundation Graduate Research Fellow, a National Defense Science and Engineering Graduate Fellow, Grand Prize winner in the 2009 Collegiate Inventors Competition, and a recipient of a National Institutes of Health Early Independence Award. Forbes magazine also named him among its “30 Under 30” in science.
To learn more about Dr. Wang (including opportunities for students and postdocs), visit his website, and see his recent paper in Molecular Systems Biology surveying new techniques for genome-scale engineering for systems and synthetic biology.
March 4, 2013
Title: Columbia Genome Center Holds High-Throughput Screening and Chemistry Symposium
On December 17, 2012, the JP Sulzberger Columbia Genome Center hosted a symposium to spotlight its capabilities in high-throughput screening. As Charles Karan, scientific director of the High-Throughput Screening Core, explained, the Genome Center is home to a suite of advanced technologies and provides access to several large collections of small molecule and shRNA probes for conducting high-throughput screens. The services that the High-Throughput Screening Core provides are available to the entire Columbia research community, helping investigators to develop and implement customized assays and to efficiently identify specific molecules of interest.
Following this overview of the Genome Center’s capabilities, the symposium also featured presentations by Columbia University faculty members Donald Landry, Brent Stockwell, Chris Henderson, and Andrea Califano, who described some advanced applications of high-throughput screening. They discussed recent basic research in the fields of stem cell biology, systems biology, and chemical biology that holds potential for improving understanding of ALS and cancer, and for improving drug discovery and optimization. Read a summary of the symposium and watch video of selected talks here.
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February 28, 2013
Title: At the Vanguard of a Revolution in Computational Genetics
Itsik Pe'er, an Associate Professor in the Department of Computer Science and member of the Columbia Initiative in Systems Biology, is using mathematics and computer analytics to identify the genetic makeup of the founding Ashkenazi Jews. By analyzing the full DNA sequences of hundreds of their descendants in the New York City area and comparing them to reference sets of non-Ashkenazi DNA, his goal is to identify Ashkenazi-specific genetic mutations associated with diseases such as Tay-Sachs, Crohn's, and Parkinson's disease. As a new article in Columbia News explains:
"By examining similarities in DNA segments shared by large numbers of related individuals, his lab developed statistical models that allow him to make generalizations about entire populations. The mix of genes that every child inherits from each parent travels in long sequences of code that remain together and are remarkably consistent from one generation to the next.
"The size of the gene chunks gets smaller with each generation, but they diminish at a consistent and predictable rate. As a result, Pe’er can use his models to determine distant relationships shared by two individuals by measuring the length of their common DNA segments."
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December 20, 2012
Title: Progress in Chemical Systems Biology
The Journal of Cancer Research has just published the proceedings of the American Association of Cancer Research Special Conference on Chemical Systems Biology. Held in Boston on June 27-30, 2012, and co-organized by Andrea Califano (Columbia University), Stuart Schreiber (Broad Institute), and Pamela Silver (Harvard Medical School), the conference spotlighted new opportunities in cancer research that are developing at the interface between chemical biology and systems biology.
Chemical systems biology has emerged as a discipline within the last few years as a result of the increasing availability of genome-wide regulatory models and the ability to perform genome-wide chemical perturbation assays. Combining these tools is enabling researchers to elucidate network-based mechanisms of tumorigenesis and disease progression in highly targeted ways. Using high-throughput technologies to rapidly compare the effects of chemical perturbations in cells with different genomic features, investigators can begin to isolate those features that play important roles in disease. This new approach is helping to identify potential new therapeutic targets for diagnosing and treating disease, as well as information about drug mechanisms of action, drug interactions, and drug synergies that could not have been found using other available methods.
The conference featured sessions on chemical biology and cancer, genome-wide sh/siRNA screening, integrative chemical and systems biology, interrogation of pathways using small molecules, approaches for sensing and perturbing pathways, recent work to study signaling pathways, and synthetic chemical biology. The final session focused on the Library of Integrated Network-Based Cellular Signatures (LINCS), a collaborative, multi-institutional project organized by the National Institutes of Health that is designed to leverage the new capabilities offered by chemical systems biology. Researchers at Columbia University and at other institutions are working to systematically identify and categorize the molecular signatures that result when cells are exposed to agents that perturb their normal function. As this information becomes available, it is being compiled into an open access database that will enable the scientific community to improve network models of disease. Learn more about the Columbia Initiative in Systems Biology's contributions to LINCS.
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November 13, 2012
Title: Connections Found between Genetic Networks for Schizophrenia and Autism
In a new paper published in the journal Nature Neuroscience, Columbia University researchers report that many of the genes that are mutated in schizophrenia are organized into two main networks. Surprisingly, the study also found that a genetic network that leads to schizophrenia is very similar to a network that has been linked to autism.
Using a computational approach called NETBAG+, Dennis Vitkup and colleagues performed network-based analyses of rare de novo mutations to map the gene networks that lead to schizophrenia. When they compared one schizophrenia network to an autism network described in a study he published last year, they discovered that different copy number variants in the same genes can lead to either schizophrenia or autism. The overlapping genes are important for processes such as axon guidance, synapse function, and cell migration -- processes within the brain that have been shown to play a role in the development of these two diseases. These gene networks are particularly active during prenatal development, suggesting that the foundations for schizophrenia and autism are laid very early in life.
Dr. Vitkup believes that there may be many more genes to be found that are tied to schizophrenia, but predicts that they will function within the networks that his team has described. In a press release from Columbia University Medical Center, he explains, "Until a few years ago, people were looking for just a handful of genes responsible for autism and schizophrenia, so the idea that many hundreds of genes are involved is a big change in thinking...Our study and the studies of our collaborators suggest that in the search for the causes of complex genetic disorders, it will be more productive to look for common pathways and gene circuits than for a handful of causal genes. This type of network analysis gives us a way to begin to make sense of what's happening."
Dr. Vitkup is an associate professor in the Department of Biomedical Informatics, the Center for Computational Biology and Bioinformatics, and the Columbia Initiative in Systems Biology. His collaborators on this study included Sarah R. Gilman, Jonathan Chang, Bin Xu, Tejdeep S. Bawa, Joseph A. Gogos, and Maria Karayiorgou, all of Columbia University Medical Center.
November 7, 2012
Title: C2B2 to Upgrade Advanced Research Computing Capabilities
The Center for Computational Biology and Bioinformatics (C2B2) has begun a major upgrade of its Advanced Research Computing core.
In the coming months, C2B2 will launch a new computing cluster that boasts 212 teraflops of performance. This figure is nearly nine times the total computing capacity of its current computing platform, called Titan. The new system will have 6,336 CPU-cores, over 70,000 CUDA-cores (GPU), and 22 TB of total system memory. The primary source of funding for this new system is a High-End Instrumentation grant from the National Institutes of Health.
The Advanced Research Computing Support (ARCS) group at the Center for Computational Biology and Bioinformatics supports research at the Columbia Initiative in Systems Biology as well as the Herbert Irving Comprehensive Cancer Center, the Institute for Cancer Genetics, and the JP Sulzberger Columbia Genome Center. This expansion of the ARCS high-performance computing environment will enable Columbia University Medical Center to meet the university's quickly growing needs for analysis of high-throughput biomedical research data.
As the Columbia Initiative in Systems Biology moves in the coming months to become a full Department of Systems Biology, the new high-performance computing platform will also support the recruitment of several new faculty members.
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October 2, 2012
Title: Uniting Structural and Systems Biology: An Interview with Barry Honig
In a new paper published in Nature magazine, Barry Honig, Andrea Califano, first authors Qiangfeng Cliff Zhang and Donald Petrey, and other members of the Columbia Initiative in Systems Biology report on the first successful integration of structural biology and systems biology. For the first time, the researchers have shown that information about protein structure can be used to make predictions about protein-protein interactions on a genome-wide scale.
Their approach capitalizes on innovative approaches in computational structural biology that the Honig lab has developed over the last 15 years, culminating in the development of a new algorithm called Predicting Protein-Protein Interactions (PrePPI). Considering protein structure within the context of computational models of cellular networks, they report, not only improves the predictive value of the researchers' models by giving another layer of evidence, but can also lead to new types of predictions that could not be made using other methods.
Read an interview with Barry Honig, in which he describes the evolution of this new approach, and what it could mean for the future of systems biology.
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September 21, 2012
Title: A First Method for Global Probabilistic Annotations of Metabolic Networks
A Columbia University team led by professor Dennis Vitkup and PhD student German Plata of the Center for Computational Biology and Bioinformatics has developed a novel genome-wide framework for making probabilistic annotations of metabolic networks. Their approach, called Global Biochemical Reconstruction Using Sampling (GLOBUS), combines information about sequence homology with context-specific information including phylogeny, gene clustering, and mRNA co-expression to predict the probability of biochemical interactions between specific genes. By integrating these different categories of information using a principled probabilistic framework, this approach overcomes limitations of considering only one functional category or one gene at a time, providing a global and accurate prediction of metabolic networks.
In a paper published in Nature Chemical Biology, the scientists write, "Currently, most publicly available biochemical databases do not provide quantitative probabilities or confidence measures for existing annotations. This makes it hard for the users of these valuable resources to distinguish between confident assignments and mere guesses... The GLOBUS approach, which is based on statistical sampling of possible biochemical assignments, provides a principled framework for such global probabilistic annotations. The method assigns annotation probabilities to each gene and suggests likely alternative functions."
To test the accuracy of GLOBUS, the Columbia researchers used it to generate genome-wide predictions about the metabolic networks in the bacteria Bacillus subtilis and Staphylococcus aureus, and selected three predictions for experimental validation. Subsequent laboratory experiments by their collaborators at ETH Zurich confirmed the predicted functions of these genes. Among the predictions is an important pathway of genes responsible for spore formation in B. subtilis.
The researchers suggest that data from GLOBUS can be easily combined with metabolomic, proteomic, and fluxomic data being generated by experimental methods. By identifying complementary patterns that appear across these different data modalities, scientists will be able to make increasingly confident predictions about the function of the genes involved in metabolism. The paper also suggests that GLOBUS could be particularly important for understanding metabolic networks in less-studied organisms.
In addition to the paper, see a News and Views commentary in Nature Chemical Biology about this novel approach.
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July 26, 2012
Title: Study Identifies a Genetic Cause of Glioblastoma
A new paper published by Columbia University Medical Center researchers in the journal Science has determined that some cases of glioblastoma, the most aggressive form of primary brain cancer, result from the fusion of the genes FGFR and TACC. Raul Rabadan, a co-senior author on the study, led efforts to identify these genes by using quantitative methods to analyze the glioblastoma genome from nine patients, and then compare these results with more than 300 genomes from the Cancer Genome Atlas project.
The collaboration with cancer genomics expert Antonio Iavarone and co-senior author Anna Lasorella found that the protein produced by the FGFR-TACC fusion disrupts the mitotic spindle (the cellular structure that guides mitosis) and causes aneuploidy, an uneven distribution of chromosomes that causes tumorigenesis. The researchers also found that drugs that target this aberration can dramatically slow the growth of tumors in mice, suggesting a potential therapeutic target.
"This work is the result of an ongoing collaboration between a traditional and a computational lab. The synergy between the two approaches allows us to tackle complex biological problems in a high-throughput fashion, providing a global view to the genome of glioblastoma," said Dr. Rabadan. For more information about the study, read the press release at Columbia University Medical Center.
Dr. Rabadan is an associate professor of biomedical informatics with appointments in the Center for Computational Biology and Bioinformatics (C2B2) and the Columbia Initiative in Systems Biology. C2B2 graduate students Joseph Minhow Chan, Jonathan Reichel, and Eric Minwei Liu were also involved in performing the computational analysis in this study.
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June 22, 2012
Title: 2012 DREAM Challenges Announced
The Dialogue for Reverse Engineering Assessments and Methods (DREAM) has announced its 2012 DREAM Challenges. Scientists with interests in systems biology, computational biology, and related disciplines are invited to submit predictions in response to four challenges:
- Network Topology and Parameter Inference Challenge
- Sage Bionetworks-DREAM Breast Cancer Prognosis Challenge
- DREAM-Phil Bowen ALS Prediction Prize4Life
- NCI-DREAM Drug Sensitivity Prediction Challenge
Learn more about the 2012 DREAM Challenges and read about DREAM at IBM Research and GenomeWeb. And please join us in participating.
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March 19, 2012
Title: Barry Honig wins Protein Society's 2012 Christian B. Anfinsen Award
Barry Honig, Professor of Biochemistry & Molecular Biophysics, Howard Hughes Medical Institute investigator, and Director of the Center for Computational Biology and Bioinformatics, was honored by The Protein Society with the Christian B. Anfinsen Award. The award, sponsored by The Aviv Family Foundation, recognizes significant technical achievements in the field of protein science. The following is an excerpt from the award citation: "Dr. Honig is the recipient of the 2012 award for his contributions to our understanding of the electrostatic properties of proteins and the development of DelPhi and GRASP, which are among the most widely used programs in structural biology. These and other computational tools from his group have enabled numerous discoveries related to protein molecular recognition, protein-membrane interactions, and protein structural stability. Honig's own recent discoveries related to cell-cell adhesion and sequence-dependent protein-DNA recognition are outstanding examples".
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October 20, 2011
Title: Vast Hidden Network Regulates Gene Expression in Cancer
For decades, scientists have thought that the primary role of messenger RNA (mRNA) is to shuttle information from the DNA to the ribosomes, the sites of protein synthesis. However, new studies now suggest that the mRNA of one gene can control, and be controlled by, the mRNA of other genes via a large pool of microRNA molecules, with dozens to hundreds of genes working together in complex self-regulating sub-networks. In work published in the journal Cell, Dr. Andrea Califano and colleagues analyzed gene expression data in glioblastoma in combination with matched microRNA profiles to uncover a posttranscriptional regulation layer of surprising magnitude, comprising more than 248,000 microRNA (miR)-mediated interactions. These include ∼7,000 genes whose transcripts act as miR “sponges”. When two genes share a set of microRNA regulators, changes in expression of one gene affects the other. If, for instance, one of those genes is highly expressed, the increase in its mRNA molecules will “sponge up” more of the available microRNAs. As a result, fewer microRNA molecules will be available to bind and repress the other gene’s mRNAs, leading to a corresponding increase in expression. Although such an effect had been previously elucidated, the range and relevance of this kind of interaction had not been characterized
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September 30, 2011
Title: Barry Honig wins DeLano Award for Computational Biosciences
Barry Honig, Professor of Biochemistry & Molecular Biophysics, Howard Hughes Medical Institute investigator, and Director of the Center for Computational Biology and Bioinformatics, was honored by The American Society for Biochemistry and Molecular Biology with the DeLano Award for Computational Biosciences for his work in macromolecular interactions in biology. The award is given to a scientist for innovative and accessible development or application of computer technology to enhance research in the life sciences at the molecular level. Dr. Honig's software tools and their underlying conceptual basis are widely used by the general biological research community to analyze the role of electrostatics in macromolecular interactions.
September 20, 2011
Title: 2011 RECOMB Systems Biology Conference and DREAM Competition
The 6th Annual DREAM competition, the 7th Annual RECOMB Satellite Conference on Systems Biology, the 8th Annual RECOMB Satellite Conference on Regulatory Genomics, and the IDIBELL Conference on Cancer Informatics will be held jointly at the IDIBELL institute, in Barcelona, Spain, on October 14-19, 2011. The four conferences aim to bring together computational and experimental scientists in the area of regulatory genomics and systems biology, to discuss current research directions, latest findings, and establish new collaborations towards a systems-level understanding of gene regulation, with particular emphasis on cancer.
http://recomb-dream2011.org/index.php/recomb2011/recombdream2011/
September 1, 2011
Title: Professor Saeed Tavazoie joins C2B2
Saeed Tavazoie, Professor at the Department of Biochemistry and Molecular Biophysics at Columbia University, has joined C2B2. Prof. Tavazoie's research focuses on understanding the organizing principles that underlie the evolution and function of molecular networks. At one scale, his work uses large-scale genome-wide observations to reveal the "nuts and bolts" of these networks and to understand how they come together to orchestrate biological behavior. At the other extreme, it aims to achieve a holistic understanding of function by considering the native ecological context in which these networks have evolved. At the highest level, his goal is to understand how molecular networks embody an internal representation of the outside world and facilitate adaptive behaviors. Dr. Tavazoie's research focuses on these problems in the context of transcriptional regulatory and genetic networks of organisms ranging from bacteria to human. In addition to using traditional experimental methods, his lab develops and employs novel technologies for making genome-wide observations, together with computational and analytic tools required to turn these observations into predictive models of the underlying biology.
Professor Tavazoie received his Ph.D. from Harvard Medical School in 2000. He joins C2B2 and Columbia University from Princeton where he was Professor in the Department of Molecular Biology and the Lewis-Sigler Institute for Integrative Genomics.
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August 1, 2011
Title: Yufeng Shen joins C2B2
Yufeng Shen, Assistant Professor at the Department of Biomedical Informatics, has joined C2B2 and the Columbia Initiative in Systems Biology. Dr. Shen's research focuses on the development and application of computational methods for the study of human genetics and disease. Specifically, his group is working in four areas, including high-throughput sequencing and de novo assembly, genetic mapping of human diseases, autoimmunity and major histocompatibility complex, pharmacogenomics and personalized treatment.
Dr. Shen received his PhD in computational biology from the Human Genome Sequencing Center at Baylor College of Medicine in 2007. In 2008 he joined Columbia University as a postdoctoral fellow.
August 1, 2011
Title: Sagi Shapira joins SBI
Sagi Shapira, Assistant Professor of Systems Biology in the Department of Microbiology and Immunology, has joined the Systems Biology Initiative (SIB) at Columbia University. Dr. Shapira's research focuses on deciphering the genetic and molecular circuitry that is at the interface of host-pathogen interactions. The goal is to understand how this circuitry controls cellular responses to infection, imparts selective pressure on viruses and affects disease progression. A mechanistic understanding of these relationships will provide important insights into cellular machinery that control basic cell biology and will have broad implications in human translational immunology and infectious disease research.
Dr. Shapira received his PhD in Immuno-Parasitology under the guidance of Christopher A. Hunter at the University of Pennsylvania in 2005 and a Masters in Public Health at Yale University in 1999. He joins Columbia from the Broad Institute where he has a post-doctoral fellow.
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June 30, 2011
Title: New Clues to the Genetics Roots of Autism
Identification of complex molecular networks underlying common human phenotypes is a major challenge of modern genetics. A new network-based method developed at the lab of Dr. Dennis Vitkup was used to identify a large biological network of genes affected by rare de novo Copy Number Variations (CNVs) in autism. The genes forming the network are primarily related to synapse development, axon targeting, and neuron motility. The identified network is strongly related to genes previously implicated in autism and intellectual disability phenotypes. These findings are consistent with the hypothesis that significantly stronger functional perturbations are required to trigger the autistic phenotype in females compared to males. Overall, the analysis of de novo variants supports the hypothesis that perturbed synaptogenesis is at the heart of autism.
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January 24, 2011
Title: Computational and functional dissection of drug targets in Melanoma
Systematic characterization of cancer genomes has revealed a staggering number of diverse alterations that differ among individuals, so that their functional importance and physiological impact remains poorly defined. In order to identify which genetic alterations are functional , the lab of Dr. Dana Pe’er has developed a novel Bayesian probabilistic algorithm, CONEXIC, to integrate copy number and gene expression data in order to identify tumor-specific “driver” aberrations, as well as the cellular processes they affect (Figure 3). In work published in the journal Cell, the new method was applied on data from Melanoma patients, identifying a list of 64 putative ‘drivers’ and the core processes affected by them. This list includes many known driver genes (e.g., MITF), which CONEXIC correctly identified and paired with their known targets. This list also includes novel ‘driver’ candidates including Rab27a and TBC1D16, both involved in protein trafficking. ShRNA-mediated silencing of these genes in short-term tumor-derived cultures determined that they are tumor dependencies and validated their computationally predicted role in melanoma (including target identification), suggesting that protein trafficking may play an important role in this malignancy.
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May 5, 2010
Title: 3RD Annual Joint Conference on Systems Biology, Regulatory Genomics and Reverse Engineering Challenges
The 5th Annual DREAM reverse engineering challenges, the 6th Annual RECOMB Satellite on Systems Biology, and the 7th Annual RECOMB Satellite on Regulatory Genomics will be held jointly at Columbia University on November 16-20, 2010. The meeting will start at 5pm on Tuesday November 16, 2010, and run till 1pm on Sunday November 20, 2010.
http://recombsat.c2b2.columbia.edu/
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April 7, 2010
Title: Harmen Bussemaker named Guggenheim Fellow
The John Simon Guggenheim Foundation has named Harmen Bussemaker, Associate Professor in Columbia's Department of Biological Sciences, as one of its 2010 Fellows. The award supports a project titled "Deciphering the language of gene expression regulation", in which Dr. Bussemaker will combine methods from biophysics and genetics in order to predict the behavior of gene regulatory networks, and test these predictions using wet lab experiments. Guggenheim Fellows are appointed on the basis of "impressive achievement in the past and exceptional promise for future accomplishment".
http://www.gf.org/about-the-foundation/the-fellowship/
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February 17, 2010
Title: Harmen Bussemaker receives Lenfest Distinguished Columbia Faculty Award
Harmen Bussemaker, Associate Professor in Columbia's Department of Biological Sciences, was one of this year's recipients of the Lenfest Distinguished Columbia Faculty Award. The awards are given annually to faculty "of unusual merit across a range of professorial activities — including scholarship, University citizenship, and professional involvement — with a primary emphasis on the instruction and mentoring of undergraduate and graduate students".
http://www.columbiaspectator.com/2010/02/17/dirks-lenfest-honor-faculty-awardees
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January 19, 2010
Title: Transcriptional network for mesenchymal transformation of brain tumors.
High-grade gliomas, such as glioblastoma, are incurable partly because the tumor cells are widely disseminated throughout the brain. This capacity for invasive growth has been associated with the expression of genes more commonly transcribed in mesenchymal cells. In work published in the Nature Journal, Antonio Iavarone, Andrea Califano and colleagues have identified a small transcription factor network that is responsible for the mesenchymal behavior of glioma cells. The authors applied a specific algorithm designed to infer causal transcription factor-target interactions to gene expression profiles from 176 samples of high-grade gliomas. They analyzed the resulting interactome with a new algorithm that enabled them to evaluate the transcription factor network in terms of a previously identified mesenchymal gene expression signature from high-grade gliomas. This identified the 53 transcription factors that are associated with regulating mesenchymal gene expression. Further analyses identified signal transducer and activator of transcription 3 (STAT3) and CAATT/enhancer binding protein-β (CEBPβ) as potential master regulators that control the expression of a substantial proportion of these mesenchymal genes. The authors conclude that systems biology approaches can be used to identify master transcription factors that are involved in malignant transformation, and such approaches could be applied to help dissect the complexity of other tumour phenotypes.
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October 29, 2009
Title: Structural nuance in the double helix and its biological role.
Although the basic structure of the double helix has been known since the classic work of Watson and Crick. it has become increasingly clear that the helix is not regular and that its shape depends on nucleotide sequence. In two recent papers in Cell and Nature, Barry Honig, Richard Mann and their colleagues in C2B2 and the Department of Biochemistry and Molecular Biophysics have shown that sequence-dependent variations in the helix shape allow DNA-binding proteins to recognize their specific binding sites. This discovery was based initially on studies of Hox proteins that play a role in determining the anterior/posterior axis of embryos. Different Hox proteins must bind their various DNA targets with high specificity, and it was unclear how this was achieved. The researchers found that Hox proteins were able to recognize the width of the minor groove through the insertion of arginines in sites where the groove was narrow (Cell, 131:530, 2007). The newest findings, published in Nature (461:1248, 2009), establish the generality of this mechanism and explain it physical origins. Specifically, short AT rich regions have an intrinsic tendency to narrow grooves and this in turn enhances the negative electrical potential of the DNA in this region, thus attracting positively charged arginines on protein surfaces. These findings are expected to have major impact on our ability to predict the DNA targets of different transcription factors.
October 16, 2009
Title: Tracking the H1N1 pandemic virus
The recent outbreak and sudden spread of a novel H1N1 influenza virus has caused a worldwide concern and has tested our ability to respond to major public health challenges. Significant scientific resources have been marshaled to discover the best possible responses against this novel swine origin influenza virus. A group led by Raul Rabadan at the Center for Computational Biology and the Department of Biomedical Informatics at Columbia University has been studying the evolution of influenza viruses and the origins of flu pandemics by analyzing large data sets that contain genomic information. After the first news of the outbreak in April 2009, the group worked intensely to decipher the origins, the diversification, and the spread of the pandemic virus, and investigated the factors that could contribute to its virulence. The results of these studies are published in major scientific journals including the New England Journal of Medicine, Eurosurveillance, PLoS, etc., and have received special attention from the media, including:
- CNN
- Reuters International
- Associated Press and ABC News
- China Radio International
The Rabadan lab was also the subject of the cover story in the Fall 2009 issue of the Columbia Magazine.
Portion of this work was performed in close collaboration with Gustavo Palacios and Ian Lipkin at Columbia University and the researchers at the Institute for Advanced Study in Princeton, New Jersey.
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November 3, 2008
Title: 3rd Annual DREAM Conference
The 3rd Annual DREAM (Dialogue for Reverse Engineering Assessments and Methods) Conference was held at the Broad Institute in Boston from October 29th to November 2nd 2008, jointly with the 5th Annual RECOMB Satellite Conference on Regulatory Genomics and the 4th Annual RECOMB Satellite Conference on Systems Biology. The meeting was organized by the Broad Institute of MIT and Harvard, and the MIT Computer Science and Artificial Intelligence Lab (CSAIL). The meeting brought together computational and experimental scientists in the area of regulatory genomics, to discuss current research directions, latest findings, and establish new collaborations towards a systems-level understanding of gene regulation. The program comprised 16 keynote presentations, 93 oral presentations selected from submitted manuscripts and 1-page abstracts, and 160 posters in four poster sessions. More than 500 participants registered attended the joint meeting, of which the vast majority attended all three meetings. Conference Chairs: Manolis Kellis (MIT), Andrea Califano Columbia University, Gustavo Stolovitzky (IBM). Organizing Commitee: Eleazar Eskin, Nir Friedman, Leroy Hood, Trey Ideker, Douglas Lauffenburger, Satoru Miyano, Eran Segal, Ron Shamir. Partner journal editors: Hillary Sussman, CSHL (Genome Research), Thomas Lemberger, EMBO (Nature MSB), Sorin Istrail, Brown University (Journal of Computational Biology).
For more information please visit the http://compbio.mit.edu/recombsat/ conference website.
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September 26, 2008
Title: Andrea Califano appointed to the NCI Board of Scientific Advisors
Andrea Califano, Professor of Biomedical Informatics, co-Director of the Center for Computational Biology and Bioinformatics, and Director of the National Center for the Multiscale Analysis of Genetic and Cellular Networks has been appointed for a 5 year term to the National Cancer Institute (NCI) Board of Scientific Advisors. The NCI Board of Scientific Advisors provide scientific advice on a wide variety of matters concerning scientific program policy, progress and future direction of the NCI’s extramural research programs, and concept review of extramural program initiatives.
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June 25, 2008
Title: C2B2 receives technical achievements awards
At the 2008 Annual Meeting of the cancer Biomedical Informatics Grid (caBIG™) initiative, members of the C2B2 software development team were recognized with awards for their technical achievements and contributions to the program, including their work in defining standards for the execution of bioinformatics workflows on caGrid (the grid infrastructure of caBIG) and in interfacing caGrid with TeraGrid, one of the largest national computational grid networks.
June 2, 2008
Title: C2B2 awarded caBIG Knowledge Center
The Center for Computational Biology and Bioinformatics (C2B2), in collaboration with the Broad Institute of MIT and Harvard, has a received a 3-year award from the National Cancer Institute to establish and operate the Molecular Analysis Tools Knowledge Center of the cancer Biomedical Informatics Grid (caBIG™) initiative. The mission of the Knowledge Center is to promote the adoption of caBIG™ technologies aiming to facilitate the discovery of the next generation of cancer diagnostics and therapeutics which will help realize the vision of molecular and personalized medicine. geWorkbench, the bioinformatics platform of the MAGNet Center, will be one of the tools supported by the Knowledge Center.
The caBIG™ initiative, overseen by the NCI Center for Biomedical Informatics and Information Technology, was conceived to advance basic and clinical research on cancer and improve clinical outcomes for patients. Information such as patient registries, tissue management data, and study results can be uploaded to the grid-based system.
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September 19, 2007
Title: Dana Pe'er Receives 2007 NIH Director's New Innovator Award
Dana Pe'er has been presented with the 2007 NIH Director's New Innovator Award (http://www.nih.gov/news/pr/sep2007/od-18a.htm). Part of an NIH Roadmap for Medical Research initiative, this award recognizes outstanding scientists who are "well-positioned to make significant — and potentially transformative — discoveries in a variety of areas”.
This award, proposed by NIH Director, Elias A. Zerhoni, M.D. was created to help new scientists fund highly innovative approaches to major research challenges that could lead to significant medical advances.
Dr. Pe'er is assistant professor of biological sciences at Columbia University, a member of the Center for Computational Biology and Bioinformatics and an investigator at the MAGNet Center. She utilizes computational and biotechnology approaches to understand how a cell’s regulatory network processes signals and how the signal processing goes wrong in cancer.
September 19, 2007
Title: 2nd Annual DREAM Conference
The 2nd Annual DREAM ( Dialogue for Reverse Engineering Assessments and Methods ) conference has been announced and will be held December 3 and 4, 2007 at the New York Academy of Sciences in New York, NY.
The conference will feature several speakers including: Tim Gardner, Ravi Iyengar, Fritz Roth, Chris Sander, Ron Shamir, Ilya Shmulevich, Mike Snyder, Peter Sorger, Ioannis Xenarios; as well as a presentation of accepted papers.
Also to be discussed will be the DREAM Challenge, which consists of 5 separate challenges composed of one or more datasets which participants used to generate predictions as to the best possible network from which the data originated. All predictions and results will be disclosed at the conference.
For more information please visit the DREAM Conference Website.
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June 4, 2007
Title: 2007 C2B2/MAGNet Annual Retreat
The 2007 annual C2B2/MAGNet Center retreat took place on April 6, at Wave Hill (http://wavehill.org) in New York city. Several of the Center's faculty members had the opportunity topresent and inform the C2B2/MAGNet community about the ongoing research in their laboratories. Presentations from the meeting are available online at: http://magnet.c2b2.columbia.edu/retreats/07/.
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February 8, 2007
Title: geWorkbench wins award
geWorkbench, the bioinformatics platform of the MAGNet Center, was recognized with an excellence award during the 2007 annual meeting of the cancer Biomedical Informatics Grid (caBIG) initiative. The geWorkbench project team was sited for "excellence in the design, planning and implementation of one of the first unrestricted open-source software projects from integrative genomics analysis".
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January 25, 2007
Title: DREAM Conference eBriefing
Meeting notes and presentations from the September 2006 DIMACS Workshop on the Dialogue on Reverse Engineering Assessment Methods (DREAM) are now available as an eBriefing on the New York Academy of Sciences web site.
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September 7, 2006
Title: Second DREAM Initiative Meeting
The MAGNet Center and the IBM Computational Biology Center (CBC) are jointly hosting the second meeting on the DREAM initiative (Dialogue on Reverse Engineering Assessment and Methods). The meeting will be held in New York, at the Wave Hill Conference Center. Program and registration details are available here. DREAM aims at the creation of a yearly workshop and database for the comparative analysis of systems biology methods and algorithms, specifically in the area of reverse engineering.
This will be the second in a series of planning workshops. The first one took place on March 2006 at the New York Academy of Sciences. A meeting report as well as the presentations from this 2 day event are now available at the Academy's web site.
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May 31, 2006
Title: geWorkbench version 1.0 released
Version 1.0 of geWorkbench, the Center's bioinformatics platform, is now available for download from the projects's web site at geworkbench.org. The site provides detailed documentation for end-users as well as programers interested in developing components for geWorkbench. A companion GForge site has also been setup to support collaborative development.
May 25, 2006
Title: First annual retreat presentations available online.
The presentations from the first annual MAGNet cetner retreat (March 2 2006, at Wave Hill [http://wavehill.org/] ) are now available online at: http://magnet.c2b2.columbia.edu/retreats/06/.
May 18, 2006
Title: GeneTegrate project site released
The GeneTegrate project provides a computational platform and a unifying semantic modeling layer to enrich, simplify and accelerate the analyses of distributed heterogeneous biological data. The project's web site is available at: http://www.genetegrate.org/
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March 9, 2006
Title: DREAM Initiative Planning Workshop
The National Center for Biomedical Computing at Columbia University (MAGNet), in collaboration with the IBM Computational Biology Center (CBC), is starting a new initiative to create a yearly workshop and database for the comparative analysis of systems biology methods and algorithms, specifically in the area of reverse engineering. A small planning workshop has been organized, which will be hosted in March by the New York Academy of Sciences in the context of their Systems Biology SIG. The meeting will convene a small number of colleagues to further explore and define the details and formats of this initiative. The goal of this planning workshop is to explore the scientific community consensus and potential interest in creating a community-driven database called DREAM (Database for Reverse Engineering Analysis and Methods) and an associated recurring workshop that will use this database for the quantitative and systematic comparison of systems biology methods and algorithms.
More information on this initiative is available here.
March 2, 2006
Title: First Annual MAGNet Retreat
The first annual MAGNet cetner retreat took place on March 2nd, at Wave Hill (http://wavehill.org) in New York city. The one day event (see agenda) provided an opportunity for the Core I, II and III investigators to present results of ongoing research related to the Center's activities. All presentations were recorded and will be soon made available as downloadable movie files from this web site.
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December 6, 2005
Title: Center tools used in mRNA stability study in yeast
In a paper published in the Proceedings of the National Academy of Sciences, Columbia University researchers and their colleagues report results of studying the genome-wide regulation of mRNA stability in yeast. Using MatrixREDUCE (a variant of the REDUCE algorithm developed by the Bussemaker lab) they managed to identify and computationally characterize the binding sites for six mRNA stability regulators in Saccharomyces cerevisiae, which include two members of the Pumilio-homology domain (Puf) family of RNA-binding proteins, Puf3p and Puf4p. Data and supporting material for the PNAS paper are available here.
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September 30, 2005
Title: MAGNet Press Release
A press release announcing the formation of MAGNet is now available.