Mark B Gerstein

Summary

Affiliation: Yale University
Country: USA

Publications

  1. pmc The GENCODE pseudogene resource
    Baikang Pei
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Genome Biol 13:R51. 2012
  2. pmc Integrating sequencing technologies in personal genomics: optimal low cost reconstruction of structural variants
    Jiang Du
    Department of Computer Science, Yale University, New Haven, Connecticut, USA
    PLoS Comput Biol 5:e1000432. 2009
  3. pmc Segmental duplications in the human genome reveal details of pseudogene formation
    Ekta Khurana
    Program in Computational Biology and Bioinformatics, Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
    Nucleic Acids Res 38:6997-7007. 2010
  4. pmc Modeling ChIP sequencing in silico with applications
    Zhengdong D Zhang
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America
    PLoS Comput Biol 4:e1000158. 2008
  5. pmc Transmembrane protein oxygen content and compartmentalization of cells
    Rajkumar Sasidharan
    Molecular Biophysics and Biochemistry Department, Yale University, New Haven, Connecticut, United States of America
    PLoS ONE 3:e2726. 2008
  6. pmc A computational approach for identifying pseudogenes in the ENCODE regions
    Deyou Zheng
    Department of Molecular Biophysics and Biochemistry, Yale University, Whitney Avenue, New Haven, CT 06520, USA
    Genome Biol 7:S13.1-10. 2006
  7. pmc Pseudofam: the pseudogene families database
    Hugo Y K Lam
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Nucleic Acids Res 37:D738-43. 2009
  8. pmc Toward a universal microarray: prediction of gene expression through nearest-neighbor probe sequence identification
    Thomas E Royce
    Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, USA
    Nucleic Acids Res 35:e99. 2007
  9. pmc Measuring the evolutionary rewiring of biological networks
    Chong Shou
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
    PLoS Comput Biol 7:e1001050. 2011
  10. pmc Genomic analysis of insertion behavior and target specificity of mini-Tn7 and Tn3 transposons in Saccharomyces cerevisiae
    Michael Seringhaus
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    Nucleic Acids Res 34:e57. 2006

Detail Information

Publications187 found, 100 shown here

  1. pmc The GENCODE pseudogene resource
    Baikang Pei
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Genome Biol 13:R51. 2012
    ..However, recent evidence suggests that many of them might have some form of biological activity, and the possibility of functionality has increased interest in their accurate annotation and integration with functional genomics data...
  2. pmc Integrating sequencing technologies in personal genomics: optimal low cost reconstruction of structural variants
    Jiang Du
    Department of Computer Science, Yale University, New Haven, Connecticut, USA
    PLoS Comput Biol 5:e1000432. 2009
    ..Our strategy should facilitate the sequencing of human genomes at maximum accuracy and low cost...
  3. pmc Segmental duplications in the human genome reveal details of pseudogene formation
    Ekta Khurana
    Program in Computational Biology and Bioinformatics, Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
    Nucleic Acids Res 38:6997-7007. 2010
    ....
  4. pmc Modeling ChIP sequencing in silico with applications
    Zhengdong D Zhang
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America
    PLoS Comput Biol 4:e1000158. 2008
    ..This enables us to identify transcription-factor binding sites in ChIP-seq data in a statistically rigorous fashion...
  5. pmc Transmembrane protein oxygen content and compartmentalization of cells
    Rajkumar Sasidharan
    Molecular Biophysics and Biochemistry Department, Yale University, New Haven, Connecticut, United States of America
    PLoS ONE 3:e2726. 2008
    ....
  6. pmc A computational approach for identifying pseudogenes in the ENCODE regions
    Deyou Zheng
    Department of Molecular Biophysics and Biochemistry, Yale University, Whitney Avenue, New Haven, CT 06520, USA
    Genome Biol 7:S13.1-10. 2006
    ..We require alignments between duplicated pseudogenes and their parents to span intron-exon junctions, and this can be used to distinguish between true duplicated and processed pseudogenes (with insertions)...
  7. pmc Pseudofam: the pseudogene families database
    Hugo Y K Lam
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Nucleic Acids Res 37:D738-43. 2009
    ..The statistics also show how the number of genes and pseudogenes in families correlates across different species. Overall, they highlight the fact that housekeeping families tend to be enriched with a large number of pseudogenes...
  8. pmc Toward a universal microarray: prediction of gene expression through nearest-neighbor probe sequence identification
    Thomas E Royce
    Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, USA
    Nucleic Acids Res 35:e99. 2007
    ..Taken together, our results provide proof-of-principle for probing nucleic acid targets with off-target, nearest-neighbor features...
  9. pmc Measuring the evolutionary rewiring of biological networks
    Chong Shou
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
    PLoS Comput Biol 7:e1001050. 2011
    ....
  10. pmc Genomic analysis of insertion behavior and target specificity of mini-Tn7 and Tn3 transposons in Saccharomyces cerevisiae
    Michael Seringhaus
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    Nucleic Acids Res 34:e57. 2006
    ..Thus, both transposons are effective tools for gene disruption, but Tn7 does so with less duplication and a more uniform distribution, better approximating the behavior of the ideal transposon...
  11. pmc Modeling the relative relationship of transcription factor binding and histone modifications to gene expression levels in mouse embryonic stem cells
    Chao Cheng
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA
    Nucleic Acids Res 40:553-68. 2012
    ..Finally, we found that the models trained solely on protein-coding genes are predictive of expression levels of microRNAs, suggesting that their regulation by TFs and HMs may share a similar mechanism to that for protein-coding genes...
  12. pmc Training set expansion: an approach to improving the reconstruction of biological networks from limited and uneven reliable interactions
    Kevin Y Yip
    Department of Computer Science, Yale University, New Haven, CT 06511, USA
    Bioinformatics 25:243-50. 2009
    ....
  13. pmc The spread of scientific information: insights from the web usage statistics in PLoS article-level metrics
    Koon Kiu Yan
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America
    PLoS ONE 6:e19917. 2011
    ..These similarities and differences shed light on the theoretical understanding of different complex systems, as well as a better design of the corresponding web applications that is of high potential marketing impact...
  14. pmc The Database of Macromolecular Motions: new features added at the decade mark
    Samuel Flores
    Department of Physics, Yale University, P O Box 208120, New Haven, CT 06520 8120, USA
    Nucleic Acids Res 34:D296-301. 2006
    ..e. active sites or highly conserved positions. Lastly, we began relating our motion classification scheme to function using descriptions from the Gene Ontology Consortium...
  15. pmc 3V: cavity, channel and cleft volume calculator and extractor
    Neil R Voss
    Department of Cell Biology, The Scripps Research Institute, CB 129, La Jolla, CA 92037, USA
    Nucleic Acids Res 38:W555-62. 2010
    ..5 A for water). The outputs are volumetric representations, both as images and downloadable files, which can be used for further analysis. The 3V server and source code are available from http://3vee.molmovdb.org...
  16. pmc Sequence variation in G-protein-coupled receptors: analysis of single nucleotide polymorphisms
    Suganthi Balasubramanian
    Department of Molecular Biophysics and Biochemistry, Yale University 266 Whitney Avenue, New Haven, CT 06520 8114, USA
    Nucleic Acids Res 33:1710-21. 2005
    ..Overall, we identify 115 SNPs in GPCRs from dbSNP that are likely to be associated with disease and thus are good candidates for genotyping in association studies...
  17. pmc Improved reconstruction of in silico gene regulatory networks by integrating knockout and perturbation data
    Kevin Y Yip
    Department of Computer Science, Yale University, New Haven, Connecticut, United States of America
    PLoS ONE 5:e8121. 2010
    ..The success of the approach demonstrates the importance of integrating heterogeneous data in network reconstruction...
  18. pmc Construction and analysis of an integrated regulatory network derived from high-throughput sequencing data
    Chao Cheng
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA
    PLoS Comput Biol 7:e1002190. 2011
    ..As more and more genome-wide ChIP-Seq and RNA-Seq data becomes available in the near future, our methods of data integration have various potential applications...
  19. pmc Interpretation of genomic variants using a unified biological network approach
    Ekta Khurana
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
    PLoS Comput Biol 9:e1002886. 2013
    ..Application of the classifier to the whole genome shows its strong potential for interpretation of variants involved in mendelian diseases and in complex disorders probed by genome-wide association studies...
  20. pmc Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool
    Haiyuan Yu
    Department of Molecular Biophysics and Biochemistry, Cellular and Developmental Biology, Yale University, CT 06520, USA
    Nucleic Acids Res 35:e8. 2007
    ..COP has been integrated with the microarray data normalization tool, ExpressYourself, which is available at http://bioinfo.mbb.yale.edu/ExpressYourself/. Together, the two can eliminate most of the common noises in microarray data...
  21. pmc The role of disorder in interaction networks: a structural analysis
    Philip M Kim
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
    Mol Syst Biol 4:179. 2008
    ..A good illustration of this trend can be found in signaling pathways and, more specifically, in kinase cascades. Finally, our findings have implications for the current controversy related to party and date-hubs...
  22. pmc Genomic analysis of the hydrocarbon-producing, cellulolytic, endophytic fungus Ascocoryne sarcoides
    Tara A Gianoulis
    Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
    PLoS Genet 8:e1002558. 2012
    ..The analyses and datasets contribute to the study of cellulose degradation and biofuel production and provide the genomic foundation for the study of a model endophyte system...
  23. pmc IQSeq: integrated isoform quantification analysis based on next-generation sequencing
    Jiang Du
    Department of Computer Science, Yale University, New Haven, Connecticut, United States of America
    PLoS ONE 7:e29175. 2012
    ..This allows one to have a modular, "plugin-able" read-generation function to support the particularities of the many evolving sequencing technologies...
  24. pmc Genomics and privacy: implications of the new reality of closed data for the field
    Dov Greenbaum
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA
    PLoS Comput Biol 7:e1002278. 2011
    ..However, teaching personal genomics with identifiable subjects in the university setting will, in turn, create additional privacy issues and social conundrums...
  25. pmc Modeling gene expression using chromatin features in various cellular contexts
    Xianjun Dong
    Program in Bioinformatics and Integrative Biology, Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605, USA
    Genome Biol 13:R53. 2012
    ..ENCODE also generated the genome-wide mapping of eleven histone marks, one histone variant, and DNase I hypersensitivity sites in seven cell lines...
  26. pmc The human proteome - a scientific opportunity for transforming diagnostics, therapeutics, and healthcare
    Marc Vidal
    University of Michigan, Ann Arbor, MI, USA
    Clin Proteomics 9:6. 2012
    ..This executive summary and the following full report describe the main discussions and outcomes of the workshop...
  27. pmc Identification of yeast cell cycle regulated genes based on genomic features
    Chao Cheng
    Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
    BMC Syst Biol 7:70. 2013
    ..To complement microarray experiments, we propose a computational method to predict cell cycle regulated genes based on their genomic features - transcription factor binding and motif profiles...
  28. pmc Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors
    Kevin Y Yip
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Genome Biol 13:R48. 2012
    ..While this large amount of data creates a valuable resource, it is nonetheless overwhelmingly complex and simultaneously incomplete since it covers only a small fraction of all human transcription factors...
  29. ncbi request reprint On sports and genes
    Gili Zilberman-Schapira
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Recent Pat DNA Gene Seq 6:180-8. 2012
    ..We discuss the considerable success, and significant drawbacks, of past research along these lines, and propose interesting directions for future research...
  30. ncbi request reprint Architecture of the human regulatory network derived from ENCODE data
    Mark B Gerstein
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA
    Nature 489:91-100. 2012
    ..The regulatory information obtained in this study will be crucial for interpreting personal genome sequences and understanding basic principles of human biology and disease...
  31. pmc Predicting protein ligand binding motions with the conformation explorer
    Samuel C Flores
    Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
    BMC Bioinformatics 12:417. 2011
    ..Often the 3D structure of the protein is available in some conformation, but binding the ligand of interest may involve a large scale conformational change which is difficult to predict with existing methods...
  32. pmc Of mice and men: phylogenetic footprinting aids the discovery of regulatory elements
    Zhaolei Zhang
    Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Avenue, New Haven, CT 06520 8114, USA
    J Biol 2:11. 2003
    ..A new study shows how much it improves the prediction of gene-regulatory elements in the human genome...
  33. pmc A statistical framework for modeling gene expression using chromatin features and application to modENCODE datasets
    Chao Cheng
    Department of Molecular Biophysics and Biochemistry, Yale University, 260 Whitney Avenue, New Haven, CT 06520, USA
    Genome Biol 12:R15. 2011
    ..Moreover, our framework reveals the positional contribution around genes (upstream or downstream) of distinct chromatin features to the overall prediction of expression levels...
  34. pmc The CRIT framework for identifying cross patterns in systems biology and application to chemogenomics
    Tara A Gianoulis
    Department of Genetics, 77 Ave of Louis Pasteur, Harvard Medical School, Boston, MA 02115, USA
    Genome Biol 12:R32. 2011
    ..Here we present an approach (CRIT) to find connections such as these and show how it can be applied in a variety of genomic contexts including chemogenomics data...
  35. pmc Uncovering trends in gene naming
    Michael R Seringhaus
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Genome Biol 9:401. 2008
    ..We categorize, for instance, those that involve a naming system transferred from another context (for example, Pavlov's dogs). We hope this analysis provides clues to better steer gene naming in the future...
  36. pmc Network security and data integrity in academia: an assessment and a proposal for large-scale archiving
    Andrew Smith
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    Genome Biol 6:119. 2005
    ....
  37. pmc Comparing protein abundance and mRNA expression levels on a genomic scale
    Dov Greenbaum
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520 8114, USA
    Genome Biol 4:117. 2003
    ..We also merge many of the available yeast protein-abundance datasets, using the resulting larger 'meta-dataset' to find correlations between protein and mRNA expression, both globally and within smaller categories...
  38. pmc BoCaTFBS: a boosted cascade learner to refine the binding sites suggested by ChIP-chip experiments
    Lu Yong Wang
    Integrated Data Systems Department, Siemens Corporate Research, 755 College Road East, Princeton, New Jersey 08540, USA
    Genome Biol 7:R102. 2006
    ..We applied BoCaTFBS within the ENCODE project and showed that it outperforms many traditional binding site identification methods (for instance, profiles)...
  39. pmc The dominance of the population by a selected few: power-law behaviour applies to a wide variety of genomic properties
    Nicholas M Luscombe
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520 8114, USA
    Genome Biol 3:RESEARCH0040. 2002
    ..Through the analysis of such inventories, it has been shown that different genomes have very different usage of parts; for example, the common folds in the worm are very different from those in Escherichia coli...
  40. pmc Comprehensive analysis of pseudogenes in prokaryotes: widespread gene decay and failure of putative horizontally transferred genes
    Yang Liu
    Department of Molecular Biophysics and Biochemistry, Yale University, PO Box 208114, New Haven, CT 06520 8114, USA
    Genome Biol 5:R64. 2004
    ..Pseudogenes often manifest themselves as disabled copies of known genes. In prokaryotes, it was generally believed (with a few well-known exceptions) that they were rare...
  41. pmc Comparative analysis of processed ribosomal protein pseudogenes in four mammalian genomes
    Suganthi Balasubramanian
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    Genome Biol 10:R2. 2009
    ..The availability of genome sequences of numerous organisms allows comparative study of pseudogenes in syntenic regions. Conservation of pseudogenes suggests that they might have a functional role in some instances...
  42. pmc Genomic analysis of membrane protein families: abundance and conserved motifs
    Yang Liu
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520 8114, USA
    Genome Biol 3:research0054. 2002
    ..To this we added a clustering of a number of predicted but unclassified membrane proteins, resulting in a total of 637 membrane protein families...
  43. pmc Systematic analysis of transcribed loci in ENCODE regions using RACE sequencing reveals extensive transcription in the human genome
    Jia Qian Wu
    Molecular, Cellular and Developmental Biology Department, KBT918, Yale University, New Haven, Connecticut 06511, USA
    Genome Biol 9:R3. 2008
    ..However, there is still much uncertainty regarding precisely what portion of the genome is transcribed, the exact structures of these novel transcripts, and the levels of the transcripts produced...
  44. pmc Identification and analysis of unitary pseudogenes: historic and contemporary gene losses in humans and other primates
    Zhengdong D Zhang
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    Genome Biol 11:R26. 2010
    ..They constitute only a small fraction of annotated pseudogenes in the human genome. However, as they represent distinct functional losses over time, they shed light on the unique features of humans in primate evolution...
  45. pmc Design principles of molecular networks revealed by global comparisons and composite motifs
    Haiyuan Yu
    Department of Molecular Biophysics and Biochemistry, Whitney Avenue, Yale University, New Haven, CT 06520, USA
    Genome Biol 7:R55. 2006
    ..Molecular networks are of current interest, particularly with the publication of many large-scale datasets. Previous analyses have focused on topologic structures of individual networks...
  46. pmc PubNet: a flexible system for visualizing literature derived networks
    Shawn M Douglas
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    Genome Biol 6:R80. 2005
    ..This feature allows one to, for example, examine a literature derived network of genes based on functional similarity...
  47. pmc mRNA expression profiles show differential regulatory effects of microRNAs between estrogen receptor-positive and estrogen receptor-negative breast cancer
    Chao Cheng
    Program in Computational Biology and Bioinformatics, Yale University, George Street, New Haven, CT 06511, USA
    Genome Biol 10:R90. 2009
    ..Given this, it is useful to define an overall metric of regulatory effect for a specific microRNA and see how this changes across different conditions...
  48. pmc PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data
    Jan O Korbel
    Gene Expression Unit, European Molecular Biology Laboratory EMBL, Meyerhofstr, Heidelberg, 69117, Germany
    Genome Biol 10:R23. 2009
    ..The simulations demonstrated high structural variant reconstruction efficiency for PEMer's coverage-adjusted multi-cutoff scoring-strategy and showed its relative insensitivity to base-calling errors...
  49. pmc Molecular sampling of prostate cancer: a dilemma for predicting disease progression
    Andrea Sboner
    Department of Pathology and Laboratory Medicine, Weill Cornell Medical Center, New York, NY, USA
    BMC Med Genomics 3:8. 2010
    ..Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models...
  50. pmc Identification of genomic indels and structural variations using split reads
    Zhengdong D Zhang
    Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA
    BMC Genomics 12:375. 2011
    ..Here we present split-read identification, calibrated (SRiC), a sequence-based method for SV detection...
  51. pmc Comparison and calibration of transcriptome data from RNA-Seq and tiling arrays
    Ashish Agarwal
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    BMC Genomics 11:383. 2010
    ..Understanding the relative merits of these technologies will help researchers select the appropriate technology for their needs...
  52. pmc Relationship between gene co-expression and probe localization on microarray slides
    Yuval Kluger
    Department of Molecular Biophysics and Biochemistry, Yale University, PO Box 208114, New Haven, CT 06520, USA
    BMC Genomics 4:49. 2003
    ..This is a potentially useful tool for evaluating co-expression of genes and extraction of useful functional and chromosomal structural information about genes...
  53. pmc The relationship between the evolution of microRNA targets and the length of their UTRs
    Chao Cheng
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    BMC Genomics 10:431. 2009
    ..Their widespread and important role in animals is gauged by estimates that approximately 25% of all genes are miRNA targets...
  54. pmc Mismatch oligonucleotides in human and yeast: guidelines for probe design on tiling microarrays
    Michael Seringhaus
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    BMC Genomics 9:635. 2008
    ..Here, we present the results of two large-scale microarray experiments on S. cerevisiae and H. sapiens genomic DNA, to explore MM oligonucleotide behavior with real sample mixtures under tiling-array conditions...
  55. pmc Efficient yeast ChIP-Seq using multiplex short-read DNA sequencing
    Philippe Lefran├žois
    Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520, USA
    BMC Genomics 10:37. 2009
    ....
  56. pmc Integration of curated databases to identify genotype-phenotype associations
    Chern Sing Goh
    Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
    BMC Genomics 7:257. 2006
    ....
  57. pmc Assessment of whole genome amplification-induced bias through high-throughput, massively parallel whole genome sequencing
    Robert Pinard
    454 Life Sciences, 20 Commercial Street, Branford CT 06405, USA
    BMC Genomics 7:216. 2006
    ..The amplification-induced bias of each method was assessed by sequencing both genomes in their entirety using the 454 Sequencing System technology and comparing the results with those obtained from unamplified controls...
  58. pmc Systematic identification of transcription factors associated with patient survival in cancers
    Chao Cheng
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
    BMC Genomics 10:225. 2009
    ..However, the association between transcription factors and cancers is largely dependent on the transcription regulatory activities rather than mRNA expression levels...
  59. pmc Identification of specificity determining residues in peptide recognition domains using an information theoretic approach applied to large-scale binding maps
    Kevin Y Yip
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
    BMC Biol 9:53. 2011
    ..They mediate protein-protein interactions by recognizing and binding short motifs in their ligands. Although a great deal is known about PRDs and their interactions, prediction of PRD specificities remains largely an unsolved problem...
  60. pmc Tiling array data analysis: a multiscale approach using wavelets
    Alexander Karpikov
    Diagnostic Radiology, Yale University, New Haven, CT, USA
    BMC Bioinformatics 12:57. 2011
    ..In doing this, we used specific wavelet basis functions, Coiflets, since their triangular shape closely resembles the expected profiles of true ChIP-chip peaks...
  61. pmc Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures
    Vadim Alexandrov
    Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Ave, New Haven, CT 06511, USA
    BMC Bioinformatics 5:2. 2004
    ..Thus far, however, they have been confined to representing 1D sequence (or the aspects of structure that could be represented by character strings)...
  62. pmc PARE: a tool for comparing protein abundance and mRNA expression data
    Eric Z Yu
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    BMC Bioinformatics 8:309. 2007
    ..Since proteins are translated from mRNAs, their expression is expected to be related to their abundance, to some degree...
  63. pmc Detection of copy number variation from array intensity and sequencing read depth using a stepwise Bayesian model
    Zhengdong D Zhang
    Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA
    BMC Bioinformatics 11:539. 2010
    ....
  64. pmc Information assessment on predicting protein-protein interactions
    Nan Lin
    Department of Mathematics, Washington University in St Louis, St Louis, MO 63130, USA
    BMC Bioinformatics 5:154. 2004
    ....
  65. pmc LinkHub: a Semantic Web system that facilitates cross-database queries and information retrieval in proteomics
    Andrew K Smith
    Department of Computer Science, Yale University, New Haven, Connecticut, 06520 USA
    BMC Bioinformatics 8:S5. 2007
    ..g. proteins) and the massive graph of relationships among them. These relationships are sometimes simple (e.g. synonyms) but are often more complex (e.g. one-to-many relationships in protein family membership)...
  66. pmc Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels
    Kevin Y Yip
    Department of Computer Science, Yale University, 51 Prospect Street, New Haven, CT 06511, USA
    BMC Bioinformatics 10:241. 2009
    ..The predictions at each level could benefit from using the features at all three levels. However, it is not trivial as the features are provided at different granularity...
  67. ncbi request reprint Integrative database analysis in structural genomics
    M Gerstein
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA
    Nat Struct Biol 7:960-3. 2000
    ..Integrative database analysis allows one to survey the 'finite parts list' of protein folds from many perspectives, highlighting certain folds and structural features that stand out in particular ways...
  68. pmc Comprehensive assessment of automatic structural alignment against a manual standard, the scop classification of proteins
    M Gerstein
    Molecular Biophysics and Biochemistry Department, Yale University, New Haven, Connecticut 06520 8114, USA
    Protein Sci 7:445-56. 1998
    ..With these improvements and systematic tests, our procedure should be useful for the development of scop and the future classification of protein folds...
  69. ncbi request reprint The current excitement in bioinformatics-analysis of whole-genome expression data: how does it relate to protein structure and function?
    M Gerstein
    Department of Molecular Biophysics and Biochemistry, 266 Whitney Avenue, Yale University, PO Box 208114, New Haven, CT 06520, USA
    Curr Opin Struct Biol 10:574-84. 2000
    ..Other attributes of proteins can also be related to expression-in particular, structure and localization-and sometimes show a clearer relationship than function...
  70. ncbi request reprint Comparing genomes in terms of protein structure: surveys of a finite parts list
    M Gerstein
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    FEMS Microbiol Rev 22:277-304. 1998
    ..Continuously updated tables and further information pertinent to this review are available over the web at http://bioinfo.mbb.yale.edu/genome...
  71. ncbi request reprint What is a gene, post-ENCODE? History and updated definition
    Mark B Gerstein
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06511, USA
    Genome Res 17:669-81. 2007
    ..It also manifests how integral the concept of biological function is in defining genes...
  72. ncbi request reprint How representative are the known structures of the proteins in a complete genome? A comprehensive structural census
    M Gerstein
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    Fold Des 3:497-512. 1998
    ..It is also important for improving database-based methods of structure prediction and genome annotation...
  73. pmc A database of macromolecular motions
    M Gerstein
    Department of Molecular Biophysics and Biochemistry, 266 Whitney Avenue, Yale University, PO Box 208114, New Haven, CT 06520, USA
    Nucleic Acids Res 26:4280-90. 1998
    ..These pathways can be viewed in a variety of movie formats, and the database is associated with a server that can automatically generate these movies from submitted coordinates...
  74. ncbi request reprint Patterns of protein-fold usage in eight microbial genomes: a comprehensive structural census
    M Gerstein
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA
    Proteins 33:518-34. 1998
    ..This implies there are no marked preferences for proteins with particular numbers of TM-helices (e.g. 7-TM) in microbial genomes...
  75. ncbi request reprint Proteomics. Integrating interactomes
    Mark Gerstein
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    Science 295:284-7. 2002
  76. ncbi request reprint Predicting interactions in protein networks by completing defective cliques
    Haiyuan Yu
    Department of Molecular Biophysics and Biochemistry, 266 Whitney Avenue, Yale University, PO Box 208114, New Haven, CT 06520 8285, USA
    Bioinformatics 22:823-9. 2006
    ..We formulate an algorithm for applying this method to large-scale networks, and show that in practice it is efficient and has good predictive performance. More information can be found on our website http://topnet.gersteinlab.org/clique/..
  77. ncbi request reprint An interdepartmental Ph.D. program in computational biology and bioinformatics: the Yale perspective
    Mark Gerstein
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
    J Biomed Inform 40:73-9. 2007
    ..Further updated information is available from the program's website, www.cbb.yale.edu.)..
  78. pmc A structural census of the current population of protein sequences
    M Gerstein
    Molecular Biophysics and Biochemistry Department, P O Box 208114, Yale University, New Haven, CT 06520 8114, USA
    Proc Natl Acad Sci U S A 94:11911-6. 1997
    ..They also have important implications for database-based methods for fold recognition, suggesting that an unknown sequence from a plant is more likely to have a certain fold (e.g., a TIM barrel) than an unknown sequence from an animal...
  79. ncbi request reprint Exploring the range of protein flexibility, from a structural proteomics perspective
    Mark Gerstein
    Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Ave, New Haven, CT 06520, USA
    Curr Opin Chem Biol 8:14-9. 2004
    ..New data emphasize a breadth of possible structural mechanisms, particularly the ability to drastically alter protein architecture and the native flexibility of many structures...
  80. pmc Structural genomics: a new era for pharmaceutical research
    Yang Liu
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520 8114, USA
    Genome Biol 3:REPORTS4004. 2002
  81. pmc Analysis of copy number variants and segmental duplications in the human genome: Evidence for a change in the process of formation in recent evolutionary history
    Philip M Kim
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA
    Genome Res 18:1865-74. 2008
    ..In addition to a coarse-grained analysis, we performed targeted sequencing of 67 CNVs and then analyzed a combined set of 270 CNVs (540 breakpoints) to verify our conclusions...
  82. pmc Annotation transfer between genomes: protein-protein interologs and protein-DNA regulogs
    Haiyuan Yu
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA
    Genome Res 14:1107-18. 2004
    ..We test a number of these in two-hybrid experiments and are able to verify 45 overlaps, which we show to be statistically significant...
  83. pmc PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls
    Joel Rozowsky
    Molecular Biophysics and Biochemistry Dept, Yale University, PO Box 208114, New Haven, Connecticut 06520 8114, USA
    Nat Biotechnol 27:66-75. 2009
    ..Our scoring procedure enables us to optimize experimental design by estimating the depth of sequencing required for a desired level of coverage and demonstrating that more than two replicates provides only a marginal gain in information...
  84. pmc Variation in transcription factor binding among humans
    Maya Kasowski
    Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520, USA
    Science 328:232-5. 2010
    ..Our results indicate that many differences in individuals and species occur at the level of TF binding, and they provide insight into the genetic events responsible for these differences...
  85. pmc Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project
    Mark B Gerstein
    Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, CT 06520, USA
    Science 330:1775-87. 2010
    ..Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome...
  86. doi request reprint Annotating non-coding regions of the genome
    Roger P Alexander
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA
    Nat Rev Genet 11:559-71. 2010
    ..Finally, one can relate functional genomics annotations to conserved units and measures of conservation derived from comparative sequence analysis...
  87. pmc Genome-wide analysis of chromatin features identifies histone modification sensitive and insensitive yeast transcription factors
    Chao Cheng
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    Genome Biol 12:R111. 2011
    ....
  88. pmc Diverse roles and interactions of the SWI/SNF chromatin remodeling complex revealed using global approaches
    Ghia M Euskirchen
    Department of Genetics, Stanford University School of Medicine, California, United States of America
    PLoS Genet 7:e1002008. 2011
    ..Taken together the results from our ChIP and immunoprecipitation experiments suggest that SWI/SNF facilitates gene regulation and genome function more broadly and through a greater diversity of interactions than previously appreciated...
  89. pmc Systematic prediction and validation of breakpoints associated with copy-number variants in the human genome
    Jan O Korbel
    Departments of Molecular Biophysics and Biochemistry, Yale University School of Medicine, New Haven, CT 06520, USA
    Proc Natl Acad Sci U S A 104:10110-5. 2007
    ..Further, it enabled us to demonstrate a clear Mendelian pattern of inheritance for one of the CNVs...
  90. pmc Prediction and characterization of noncoding RNAs in C. elegans by integrating conservation, secondary structure, and high-throughput sequencing and array data
    Zhi John Lu
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA
    Genome Res 21:276-85. 2011
    ..Overall, our study identifies many new potential ncRNAs in C. elegans and provides a method that can be adapted to other organisms...
  91. pmc MOTIPS: automated motif analysis for predicting targets of modular protein domains
    Hugo Y K Lam
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    BMC Bioinformatics 11:243. 2010
    ..However, predicting domain targets by motif sequence alone without considering other genomic and structural information has been shown to be lacking in accuracy...
  92. ncbi request reprint An integrated approach for finding overlooked genes in yeast
    Anuj Kumar
    Department of Molecular, Cellular, and Developmental Biology, Yale University, P O Box 208103, New Haven, CT 06520 8103, USA
    Nat Biotechnol 20:58-63. 2002
    ..In total, the genes discovered using this approach constitute 2% of the yeast genome and represent a wealth of overlooked biology...
  93. ncbi request reprint Relating three-dimensional structures to protein networks provides evolutionary insights
    Philip M Kim
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    Science 314:1938-41. 2006
    ....
  94. pmc Analysis of membrane proteins in metagenomics: networks of correlated environmental features and protein families
    Prianka V Patel
    Department of Molecular Biophysics, Yale University, New Haven, Connecticut 06520, USA
    Genome Res 20:960-71. 2010
    ....
  95. pmc StoneHinge: hinge prediction by network analysis of individual protein structures
    Kevin S Keating
    Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA
    Protein Sci 18:359-71. 2009
    ..By comparison, a popular hinge detection method that requires knowledge of both the open and closed conformations finds 10 of the 13 known hinges, while predicting four additional, false hinges...
  96. pmc Paired-end mapping reveals extensive structural variation in the human genome
    Jan O Korbel
    Molecular Biophysics and Biochemistry Department, Yale University, New Haven, CT 06520, USA
    Science 318:420-6. 2007
    ..The breakpoint junction sequences of more than 200 SVs were determined with a novel pooling strategy and computational analysis. Our analysis provided insights into the mechanisms of SV formation in humans...
  97. pmc Comprehensive analysis of amino acid and nucleotide composition in eukaryotic genomes, comparing genes and pseudogenes
    Nathaniel Echols
    Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Avenue, Box 208114, New Haven, CT 06520 8114, USA
    Nucleic Acids Res 30:2515-23. 2002
    ..Our compositional analyses with the interactive viewer are available over the web at http://genecensus.org/pseudogene...
  98. pmc Nucleotide-resolution analysis of structural variants using BreakSeq and a breakpoint library
    Hugo Y K Lam
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA
    Nat Biotechnol 28:47-55. 2010
    ..As new data become available, we expect our BreakSeq approach will become more sensitive and facilitate rapid SV genotyping of personal genomes...
  99. pmc Analysis of genomic variation in non-coding elements using population-scale sequencing data from the 1000 Genomes Project
    Xinmeng Jasmine Mu
    Program in Computational Biology and Bioinformatics, Department of Molecular Biophysics and Biochemistry, W M Keck Foundation Biotechnology Resource Laboratory, Yale University, New Haven, CT 06520, USA
    Nucleic Acids Res 39:7058-76. 2011
    ....