Mark B Gerstein

Summary

Affiliation: Yale University
Country: USA

Publications

  1. 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
  2. pmc The real cost of sequencing: higher than you think!
    Andrea Sboner
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Genome Biol 12:125. 2011
  3. 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
  4. 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
  5. 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
  6. 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
  7. doi 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
  8. 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
  9. 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
  10. 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

Collaborators

Detail Information

Publications169 found, 100 shown here

  1. 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...
  2. pmc The real cost of sequencing: higher than you think!
    Andrea Sboner
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Genome Biol 12:125. 2011
    ..Advances in sequencing technology have led to a sharp decrease in the cost of 'data generation'. But is this sufficient to ensure cost-effective and efficient 'knowledge generation'?..
  3. 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...
  4. 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...
  5. 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...
  6. 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...
  7. doi 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...
  8. 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...
  9. 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...
  10. 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...
  11. 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...
  12. 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...
  13. 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
    ....
  14. 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...
  15. 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)...
  16. 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...
  17. 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...
  18. 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...
  19. 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...
  20. 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...
  21. 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...
  22. 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...
  23. 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...
  24. 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...
  25. 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...
  26. 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...
  27. 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...
  28. 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...
  29. 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...
  30. 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...
  31. 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...
  32. 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
    ....
  33. 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
    ....
  34. 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...
  35. 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...
  36. 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...
  37. 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...
  38. 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)...
  39. 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...
  40. 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
    ....
  41. 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
    ....
  42. 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)...
  43. 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...
  44. 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/..
  45. 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...
  46. 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.)..
  47. 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...
  48. 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
  49. 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
  50. 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...
  51. 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...
  52. 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...
  53. 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...
  54. 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...
  55. 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...
  56. 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...
  57. 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...
  58. 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...
  59. 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...
  60. 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...
  61. 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
    ....
  62. 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...
  63. 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...
  64. 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...
  65. 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...
  66. 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...
  67. 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...
  68. 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...
  69. 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...
  70. 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...
  71. doi request reprint HingeMaster: normal mode hinge prediction approach and integration of complementary predictors
    Samuel C Flores
    Department of Physics, Yale University, New Haven, Connecticut 06520, USA
    Proteins 73:299-319. 2008
    ..We integrated all the methods into a combined predictor using a weighted voting scheme. Finally, we encapsulated all our results in a web tool which can be used to run all the predictors on submitted proteins and visualize the results...
  72. ncbi request reprint Structural genomics analysis: characteristics of atypical, common, and horizontally transferred folds
    Hedi Hegyi
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA
    Proteins 47:126-41. 2002
    ..In particular, we find three possible examples of transfer between archaea and bacteria and six between eukarya and bacteria. We make available our detailed results at http://genecensus.org/20...
  73. 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
    ....
  74. 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...
  75. 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...
  76. 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...
  77. pmc FlexOracle: predicting flexible hinges by identification of stable domains
    Samuel C Flores
    Department of Physics, Yale University, Bass 432, New Haven, CT 06520, USA
    BMC Bioinformatics 8:215. 2007
    ..Programs such as GNM and FIRST have made global flexibility predictions available at low computational cost, but are not designed specifically for finding hinge points...
  78. pmc Analysis of combinatorial regulation: scaling of partnerships between regulators with the number of governed targets
    Nitin Bhardwaj
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
    PLoS Comput Biol 6:e1000755. 2010
    ..Finally, we perform various down-sampling calculations on the observed data to illustrate the robustness of our conclusions...
  79. pmc TopNet: a tool for comparing biological sub-networks, correlating protein properties with topological statistics
    Haiyuan Yu
    Department of Molecular Biophysics and Biochemistry, 266 Whitney Avenue, Yale University, PO Box 208114, New Haven, CT 06520, USA
    Nucleic Acids Res 32:328-37. 2004
    ..This phenomenon may reflect the incompleteness of the experimentally determined yeast interaction network...
  80. ncbi request reprint Helix Interaction Tool (HIT): a web-based tool for analysis of helix-helix interactions in proteins
    Anne E Counterman Burba
    Department of Molecular Biophysics and Biochemistry, Yale University New Haven, CT 06520, USA
    Bioinformatics 22:2735-8. 2006
    ..For the latter purpose, a direct interface from entries in the Molecular Motions Database to the HIT site has been provided...
  81. ncbi request reprint A supervised hidden markov model framework for efficiently segmenting tiling array data in transcriptional and chIP-chip experiments: systematically incorporating validated biological knowledge
    Jiang Du
    Department of Computer Science, Yale University, New Haven, CT 06520, USA
    Bioinformatics 22:3016-24. 2006
    ..Here we propose a supervised framework for doing this. It has the advantage of explicitly incorporating validated biological knowledge into the model and allowing for formal training and testing...
  82. 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...
  83. pmc Mapping of transcription factor binding regions in mammalian cells by ChIP: comparison of array- and sequencing-based technologies
    Ghia M Euskirchen
    Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut 06520 8103, USA
    Genome Res 17:898-909. 2007
    ..Overall, this study provides information for robust identification, scoring, and validation of TF targets using ChIP-based technologies...
  84. 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
    ....
  85. pmc Assessing the performance of different high-density tiling microarray strategies for mapping transcribed regions of the human genome
    Olof Emanuelsson
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520 8114, USA
    Genome Res 17:886-97. 2007
    ..Finally, our experiments reveal a significant amount of novel transcription outside of known genes, and an appreciable sample of this was validated by independent experiments...
  86. ncbi request reprint Analysis of mRNA expression and protein abundance data: an approach for the comparison of the enrichment of features in the cellular population of proteins and transcripts
    Dov Greenbaum
    Department Genetics, 266 Whitney Avenue, Yale University, PO Box 208114, New Haven, CT 06520, USA
    Bioinformatics 18:585-96. 2002
    ..Furthermore, it will be essential to integrate, within a common framework, the results of many varied experiments by different investigators. This will allow one to survey the characteristics of highly expressed genes and proteins...
  87. 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...
  88. pmc The transcriptional landscape of the yeast genome defined by RNA sequencing
    Ugrappa Nagalakshmi
    Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520, USA
    Science 320:1344-9. 2008
    ..We also found unexpected 3'-end heterogeneity and the presence of many overlapping genes. These results indicate that the yeast transcriptome is more complex than previously appreciated...
  89. 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
    ....
  90. pmc Statistical analysis of the genomic distribution and correlation of regulatory elements in the ENCODE regions
    Zhengdong D Zhang
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA
    Genome Res 17:787-97. 2007
    ..Data sets associated with histone modifications have particularly strong correlations. Finally, we show how the correlations between factors change when only regulatory elements far from the transcription start sites are considered...
  91. pmc Analysis of diverse regulatory networks in a hierarchical context shows consistent tendencies for collaboration in the middle levels
    Nitin Bhardwaj
    Program in Computational Biology and Bioinformatics, Yale University, Bass 426, 266 Whitney Avenue, New Haven, CT 06520, USA
    Proc Natl Acad Sci U S A 107:6841-6. 2010
    ..There is, however, one notable difference between networks in different species: The amount of collaborative regulation and democratic character increases markedly with overall genomic complexity...
  92. doi request reprint Novel insights through the integration of structural and functional genomics data with protein networks
    Declan Clarke
    Department of Chemistry, Yale University, New Haven, CT 06520, USA
    J Struct Biol 179:320-6. 2012
    ....
  93. pmc The DART classification of unannotated transcription within the ENCODE regions: associating transcription with known and novel loci
    Joel S Rozowsky
    Molecular Biophysics and Biochemistry Department, Yale University, New Haven, Connecticut 06520 8114, USA
    Genome Res 17:732-45. 2007
    ..Overall, we find that 18 of the 46 connections tested validate by RT-PCR and four of five sequenced PCR products confirm connectivity unambiguously...
  94. pmc Integrated assessment of genomic correlates of protein evolutionary rate
    Yu Xia
    Bioinformatics Program, Boston University, Boston, Massachusetts, USA
    PLoS Comput Biol 5:e1000413. 2009
    ..Our integrated assessment framework can be readily extended to other correlational analyses at the genome scale...
  95. pmc Hinge Atlas: relating protein sequence to sites of structural flexibility
    Samuel C Flores
    Department of Physics, Yale University, New Haven, CT, USA
    BMC Bioinformatics 8:167. 2007
    ..Efforts in this field have been hampered by the lack of a proper dataset for studying characteristics of hinges...
  96. pmc Integration of protein motions with molecular networks reveals different mechanisms for permanent and transient interactions
    Nitin Bhardwaj
    Yale University, New Haven, Connecticut 06520, USA
    Protein Sci 20:1745-54. 2011
    ..We provide evidence for this hypothesis through showing that interfaces involved in transient interactions bind fewer classes of domains than those in a control set...
  97. pmc Positive selection at the protein network periphery: evaluation in terms of structural constraints and cellular context
    Philip M Kim
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    Proc Natl Acad Sci U S A 104:20274-9. 2007
    ..e., extracellular space or cell membrane). This suggests that the observed positive selection at the network periphery may be due to an increase of adaptive events on the cellular periphery responding to changing environments...
  98. ncbi request reprint Digging deep for ancient relics: a survey of protein motifs in the intergenic sequences of four eukaryotic genomes
    Zhao Lei Zhang
    Department of Molecular Biophysics and Biochemistry, Yale University, Bass Center 432A, 266 Whitney Avenue, P O Box 208114, New Haven, CT 06520 8114, USA
    J Mol Biol 323:811-22. 2002
    ..Moreover, we find that in aggregate the over-represented pseudomotif patterns occupy a substantial fraction of the intergenic regions. Further information is available at http://pseudogene.org..
  99. pmc Differential binding of calmodulin-related proteins to their targets revealed through high-density Arabidopsis protein microarrays
    Sorina C Popescu
    Department of Molecular, Cellular, and Developmental Biology, Yale University, 219 Prospect Street, New Haven, CT 06520 8103, USA
    Proc Natl Acad Sci U S A 104:4730-5. 2007
    ..Our results suggest that calcium functions through distinct CaM/CML proteins to regulate a wide range of targets and cellular activities...
  100. ncbi request reprint A small reservoir of disabled ORFs in the yeast genome and its implications for the dynamics of proteome evolution
    Paul Harrison
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520 8114, USA
    J Mol Biol 316:409-19. 2002
    ..See genecensus.org/pseudogene for further information.)..
  101. ncbi request reprint Transcription factor binding site identification in yeast: a comparison of high-density oligonucleotide and PCR-based microarray platforms
    Anthony R Borneman
    Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA
    Funct Integr Genomics 7:335-45. 2007
    ..The HDO array platform provides a far more robust array system by all measures than PCR-based arrays, all of which is directly attributable to the large number of probes available...