0008816770 http://papers.gersteinlab.org/e-print//preprint.pdf issue-overview-cosb Sequences and Topology M Gerstein, B Honig Current Opinion in Structural Biology 2001 11 327-329 http://papers.gersteinlab.org/e-print/issue-overview-cosb/text.pdf 11406382 75 epub An analysis of the present system of scientific publishing: what's wrong and where to go from here D Greenbaum, J Lim, M Gerstein. Interdiscip Sci Rev. (in press) http://papers.gersteinlab.org/e-print/epub/text.pdf D Greenbaum, J Lim, M Gerstein Interdiscip Sci Rev 2003 28 293-302 epublishing paperdeath The Death of the Scientific Paper Seringhaus M, Gerstein M (2006). The Scientist. 20(9): 25 http://papers.gersteinlab.org/e-print/paperdeath/preprint.pdf keck 2006 2006-summary,epublishing http://www.the-scientist.com/2006/9/1/25/1/ yeast-hub An XML-Based Approach to Integrating Heterogeneous Yeast Genome Data KH Cheung, D Pan, A Smith, M Seringhaus, SM Douglas, M Gerstein. 2004 International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences (METMBS); pp 236-242 http://papers.gersteinlab.org/e-print/yeast-hub/preprint.pdf 2004 nsfymd 2004-summary,interrelate,student http://yeasthub.gersteinlab.org funcgrid Towards a systematic definition of protein function that scales to the genome level: Defining function in terms of interactions. N Lan, R Jansen, M Gerstein (2002). Proceedings of the IEEE 90:1848-1858 nesg 90 1848-1858 2002 http://papers.gersteinlab.org/e-print/funcgrid/reprint.pdf http://partslist.org/func geom-inttab Protein Geometry: Distances, Areas, and Volumes http://bioinfo.mbb.yale.edu/geometry http://www.iucr.org/iucr-top/it/itf/itf.html http://papers.gersteinlab.org/e-print/geom-inttab/preprint.pdf (Volume F, Chapter 22.1.1, pages 531-539; M Rossmann & E Arnold, editors; Dordrecht: Kluwer) International Tables for Crystallography 2001 M Gerstein, F M Richards volumes 81 mem semweb-dbinteg Semantic Web Approach to Database Integration in the Life Sciences KH Cheung, AK Smith, KYL Yip, CJO Baker, MB Gerstein (2007) in Semantic Web: Revolutionizing Knowledge Discovery in the Life Sciences (eds. C Baker and K Cheung, Springer, NY), pp. 11-30 http://papers.gersteinlab.org/e-print/semweb-dbinteg/preprint.pdf keck 2007-summary,epublishing http://www.cs.concordia.ca/~baker/SW-RKDLS-May-2006.htm 2007 Motions in a Database Framework: from Structure to Sequence M Gerstein, R Jansen, T Johnson, J Tsai, W Krebs 1999 Rigidity Theory and Applications 401-442 (ed. M F Thorpe and P M Duxbury, Kluwer Academic/Plenum Publishers) http://papers.gersteinlab.org/e-print/rigidity-conf.pdf rigidity-conf http://bioinfo.mbb.yale.edu/MolMovDB 51 lesk-review-tibs http://papers.gersteinlab.org/e-print/lesk-review-tibs/index.txt A Bauhaus for Biologists: An Introduction to Protein Architecture by A. M. Lesk P Harrison, M Gerstein Trends Biochem Sci 26 204-205 2001 80 CoarseSurf A Resolution-Sensitive Procedure for Comparing Protein Surfaces and its Application to the Comparison of Antigen-Combining Sites. M Gerstein (1992) Acta Crystallographica A48: 271-276. 1992 http://bioinfo.mbb.yale.edu/hyper/mbg/CoarseSurf/ http://papers.gersteinlab.org/e-print/CoarseSurf/preprint.pdf sim-h2o-prot-helix Simulation of Water around a Model Protein Helix. 1. Two-dimensional Projections of Solvent Structure. M Gerstein, R Lynden-Bell (1993) Journal of Physical Chemistry 97: 2982-2991. 1993 http://papers.gersteinlab.org/e-print/sim-h2o-prot-helix/preprint.pdf qloc-ijqc http://papers.gersteinlab.org/e-print/qloc-ijqc/text.pdf http://bioinfo.mbb.yale.edu/genome/localize http://www3.interscience.wiley.com/cgi-bin/fulltext/85008594/FILE?TPL=ftx_start V Alexandrov, M Gerstein International Journal of Quantum Chemistry 693-696 85 2001 Calculating populations of subcellular compartments using density matrix formalism 85 ijcnnn Inferring Protein-Protein Interactions Using Interaction Network Topologies A Paccanaro, V Trifonov, H Yu, M Gerstein (2005). International Joint Conference on Neural Networks (IJCNN, Jul. 31-Aug. 4, Montreal, Canada), pages 161 - 166, vol. 1 http://papers.gersteinlab.org/e-print/ijcnnn/preprint.pdf interactions 2005 webantitrust Semantic Web Standards: Legal and Social Issues and Implications D Greenbaum, M Gerstein (2007) in Semantic Web: Revolutionizing Knowledge Discovery in the Life Sciences (eds. C Baker and K Cheung, Springer, NY), pp. 413-433 http://papers.gersteinlab.org/e-print/webantitrust/preprint.pdf keck 2007-summary,epublishing http://www.cs.concordia.ca/~baker/SW-RKDLS-May-2006.htm 2007 powerlaw-analytic Analytical Evolutionary Model for Protein Fold Occurrence in Genomes, Accounting for the Effects of Gene Duplication, Deletion, Acquisition and Selective Pressure M Kamal, N Luscombe, J Qian, M Gerstein (2006) in Power Laws, Scale-Free Networks and Genome Biology (edited by EV Koonin, YI Wolf, GP Karev; Springer, New York), pages 165-193 http://papers.gersteinlab.org/e-print/powerlaw-analytic/reprint.pdf 2006 2006-summary transmemb-oxy-content Transmembrane protein oxygen content and compartmentalization of cells. R Sasidharan, A Smith and MB Gerstein (in press) PLoS One whatis-imia What is Bioinformatics? A Proposed Definition and Overview of the Field Intl. Medical Informatics Association 2001 N Luscombe, D Greenbaum, M Gerstein http://bioinfo.mbb.yale.edu/what-is-it http://papers.gersteinlab.org/e-print/whatis-imia (Yearbook, Pages 83-99) 74 epub-debate-nature Blurring the boundaries between scientific 'papers' and biological databases Nature Yearbook of Science and Technology M Gerstein, J Junker 210-212 (ed. D Butler, Palgrave Macmillan Publishers) 2002 http://papers.gersteinlab.org/e-print/epub-debate-nature/text.html http://www.nature.com/nature/debates/e-access http://www.palgrave-usa.com/catalogue/index.asp?isbn=0333971477 ISBN 0-333-971-97147-7 epublishing xml-bibe An XML Application for Genomic Data Interoperation Cheung KH, Liu Y, Kumar K, Snyder M, Gerstein M, Miller P. IEEE International Symposium on Bio-Informatics and Biomedical Engineering (BIBE) 2001, pp. 97-103 2001 http://papers.gersteinlab.org/e-print/xml-bibe/reprint.pdf purcell-nmr Purcell's early work on NMR: Contingency versus Inevitability M Gerstein (1994) American Journal of Physics 62: 596-601 1994 epublishing http://bioinfo.mbb.yale.edu/hyper/mbg/Purcell/ http://papers.gersteinlab.org/e-print/purcell-nmr/preprint.pdf intint-chapter Protein Interaction Prediction by Integrating Genomic Features and Protein Interaction Network Analysis LJ Lu, Y Xia, H Yu, A Rives, H Lu, F Schubert, M Gerstein (2005). Data Analysis and Visualization in Genomics and Proteomics (Wiley, NY) http://papers.gersteinlab.org/e-print/intint-chapter/preprint.pdf 2005 2005-Summary,interactions,student http://networks.gersteinlab.org/intint/ inv-prob-synch-rad Inverse Problem for Synchrotron Radiation in the Presence of Noise N Fisch, A Kritz, M Gerstein (1987) Proceedings of the Sixth Joint Workshop on Electron Cyclotron Emission and Electron Cyclotron Resonance Heating. (eds. A Riviere, A Costley), 23-30 (Oxford, 16-17 September). http://papers.gersteinlab.org/e-print/inv-prob-synch-rad/preprint.pdf 1987 cyberlaw Practicing Cyberlaw in the Year 2000. R Becker, M Gerstein (1996) New Jersey Lawyer Magazine 179: 12-27 (September). http://papers.gersteinlab.org/e-print/cyberlaw/preprint.pdf 1996 tiling-wabi Fast optimal genome tiling with applications to microarray design and homology search. P Berman, P Bertone, B DasGupta, M Gerstein, M-Y Kao, M Snyder P Berman, P Bertone, B DasGupta, M Gerstein, M-Y Kao, M Snyder. (2002) Proceedings of the 2nd International Workshop on Algorithms in Bioinformatics. Springer-Verlag LNCS 2452: 419-433 2002 http://papers.gersteinlab.org/e-print/tiling-wabi/all.pdf http://www.dis.uniroma1.it/~algo02 cegs microarray changing-charge Keeping the Shape but Changing the Charges: A Simulation Study of Urea and its Isosteric Analogues J Tsai, M Gerstein, M Levitt (1996) Journal of Chemical Physics 104: 9417-9430 1996 http://papers.gersteinlab.org/e-print/changing-charge/preprint.pdf sim-h2o-prot-helix-2 Simulation of Water around a Model Protein Helix. 2. The Relative Contributions of Packing, Hydrophobicity, and Hydrogen Bonding. M Gerstein, R Lynden-Bell (1993) Journal of Physical Chemistry 97: 2991-2999. 1993 http://papers.gersteinlab.org/e-print/sim-h2o-prot-helix-2/preprint.pdf chip-seq-simu Modeling ChIP sequencing in silico with applications ZD Zhang, J Rozowsky, M Snyder, J Chang, M Gerstein (In press) PLoS Computational Biology 18528383 2008 06 05

1476-4687 453 7196 2008 Jun 5 Nature Genomics: protein fossils live on as RNA. 729-31 Sasidharan Rajkumar R Gerstein Mark M eng Comment News

England Nature 0410462 IM 2008 6 6 9 0 2008 6 6 9 0 ppublish 453729a 10.1038/453729a 18528383 sirnapgene 18528383 Genomics: protein fossils live on as RNA. Sasidharan R, Gerstein M (2008) Nature http://papers.gersteinlab.org/e-print/sirnapgene/preprint.pdf 18511261 2008 06 16

0959-440X 18 3 2008 Jun Curr. Opin. Struct. Biol. The current excitement about copy-number variation: how it relates to gene duplications and protein families. 366-74 Following recent technological advances there has been an increasing interest in genome structural variants (SVs), in particular copy-number variants (CNVs) - large-scale duplications and deletions. Although not immediately evident, CNV surveys make a conceptual connection between the fields of population genetics and protein families, in particular with regard to the stability and expandability of families. The mechanisms giving rise to CNVs can be considered as fundamental processes underlying gene duplication and loss; duplicated genes being the results of 'successful' copies, fixed and maintained in the population. Conversely, many 'unsuccessful' duplicates remain in the genome as pseudogenes. Here, we survey studies on CNVs, highlighting issues related to protein families. In particular, CNVs tend to affect specific gene functional categories, such as those associated with environmental response, and are depleted in genes related to basic cellular processes. Furthermore, CNVs occur more often at the periphery of the protein interaction network. In comparison, protein families associated with successful and unsuccessful duplicates are associated with similar functional categories but are differentially placed in the interaction network. These trends are likely reflective of CNV formation biases and natural selection, both of which differentially influence distinct protein families. Molecular Biophysics and Biochemistry Department, Yale University, New Haven, CT 06520, USA; European Molecular Biology Laboratory, D-69117 Heidelberg, Germany. Korbel Jan O JO Kim Philip M PM Chen Xueying X Urban Alexander Eckehart AE Weissman Sherman S Snyder Michael M Gerstein Mark B MB eng Journal Article 2008 05 27

England Curr Opin Struct Biol 9107784 IM 2008 1 6 2008 2 13 2008 5 27 2008 5 31 9 0 2008 5 31 9 0 ppublish S0959-440X(08)00039-0 10.1016/j.sbi.2008.02.005 18511261 cosbcnv 18511261 The current excitement about copy-number variation: how it relates to gene duplications and protein families. JO Korbel, PM Kim, X Chen, AE Urban, S Weissman, M Snyder, MB Gerstein (2008) Curr Opin Struct Biol http://papers.gersteinlab.org/e-print/cosbcnv/preprint.pdf 18487680 2008 5 19

1535-9484 2008 May 18 Mol. Cell Proteomics Targeting the human cancer pathway protein interaction network by structural genomics. Structural genomics provides an important approach for characterizing and understanding systems biology. As a step towards better integrating protein three-dimensional (3D) structural information in cancer systems biology, we have constructed a Human Cancer Pathway Protein Interaction Network (HCPIN) by analysis of several classical cancer-associated signaling pathways and their physical protein-protein interactions. Many well-known cancer-associated proteins play central roles as "hubs" or "bottlenecks" in the HCPIN. At least half of HCPIN proteins are either directly associated with or interact with multiple signaling pathways. While some 45% of residues in these proteins are in sequence segments that meet criteria sufficient for approximate homology modeling (Blast E-val < 10-6), only ~ 20% of residues in these proteins are structurally covered using high-accuracy homology modeling criteria (i.e. Blast E_val < 10-6 and at least 80% sequence identity) or by actual experimental structures. The HCPIN website (http://nmr.cabm.rutgers.edu/hcpin) provides a comprehensive description of this biomedical important multi-pathway network, together with experimental and homology models of HCPIN proteins useful for cancer biology research. In order to complement and enrich cancer systems biology, the Northeast Structural Genomics Consortium (NESG) (www.nesg.org) is targeting > 1,000 human proteins and protein domains from the HCPIN for sample production and 3D structure determination. The long-range goal of this effort is to provide a comprehensive 3D structure-function database for human cancer-associated proteins and protein complexes, in the context of their interaction networks. The network-based target selection (BioNet) approach described here is an example of a general strategy for targeting co-functioning proteins by structural genomics projects. Center for advanced biotechnology and medicine, Rutgers University, Piscataway, NJ 08854. Huang Yuanpeng Janet YJ Hang Dehua D Lu Long Jason LJ Tong Liang L Gerstein Mark B MB Montelione Gaetano T GT ENG JOURNAL ARTICLE 2008 5 18

Mol Cell Proteomics 101125647 2008 5 20 9 0 2008 5 20 9 0 aheadofprint M700550-MCP200 10.1074/mcp.M700550-MCP200 18487680 hcpin 18487680 Targeting the human cancer pathway protein interaction network by structural genomics. Huang YJ, Hang D, Lu LJ, Tong L, Gerstein MB, Montelione GT (2008) Mol Cell Proteomics http://papers.gersteinlab.org/e-print/hcpin/preprint.pdf nesg 18487515 2008 5 19

1088-9051 2008 May 16 Genome Res. A Genomics Analysis of RNA polymerase II modification and chromatin architecture related to 3' end RNA polyadenylation. Genomic analyses have been applied extensively to analyze the process of transcription initiation in mammalian cells, but much less to the events associated with transcript 3'end formation and transcription termination. We have used a novel approach to prepare 3' end fragment libraries from polyadenylated RNA of several cell types, and globally mapped the position of the poly(A) addition site using oligonucleotide arrays tiling one percent of the human genome. This approach revealed more 3' ends than had been previously annotated. The distribution of these ends relative to DNA sites bound by RNA polymerase II and the distributions with those for di- and trimethylated lysine 4 and lysine 36 of histone 3, was compared by ChIP-chip analysis. We found that a substantial fraction of unannotated 3' ends of RNA are intronic and reside antisense to the embedding gene. Poly(A) ends of annotated messages lie at a variable distance averaging approximately two kb upstream of the end of RNA polymerase binding (termination). Near the sites of RNA polymerase termination, as well as in some internal sites, there is an accumulation of both unphosphorylated and carboxy-terminal domain (CTD) serine 2 phosphorylated large subunit of polymerase II, suggesting pausing of the polymerase and perhaps dephosphorylation prior to release. Lysine 36 trimethylation occurs across the body of many transcribed genes, sometimes alternating with stretches of DNA in which lysine36 dimethylation is relatively more prominent. Lysine 36 methylation often decreases beginning at or near the site of polyadenylation, sometimes disappearing before disappearance of phosphorylated RNA polymerase II and release of RNA polymerase from DNA. Our results suggest that transcription termination may involve the separable events of loss of histone3 lysine 36 methylation and later release of RNA polymerase. The latter is often associated with polymerase pausing before release. Thus, overall our study reveals extensive sites of poly(A) addition across the human genome and provides insights into the events that may occur during 3' end formation. Yale University School of Medicine; Lian Zheng Z Karpikov Alexander A Lian Jin J Mahajan Milind C MC Hartman Stephen S Gerstein Mark M Snyder Michael M Weissman Sherman M SM ENG JOURNAL ARTICLE 2008 5 16

Genome Res 9518021 2008 5 20 9 0 2008 5 20 9 0 aheadofprint gr.075804.107 10.1101/gr.075804.107 18487515 3prime 18487515 A Genomics Analysis of RNA polymerase II modification and chromatin architecture related to 3' end RNA polyadenylation. Z Lian, A Karpikov, J Lian, MC Mahajan, S Hartman, M Gerstein, M Snyder, SM Weissman (2008) Genome Res http://papers.gersteinlab.org/e-print/3prime/preprint.pdf 18478571 2008 06 03

1097-0215 123 3 2008 Aug 1 Int. J. Cancer Association of cytokeratin 7 and 19 expression with genomic stability and favorable prognosis in clear cell renal cell cancer. 569-76 The purpose of our study was to demonstrate that distinct cytogenetic alterations in the most common subtype of renal cell cancer, clear cell renal cell carcinoma (ccRCC), are reflected in protein expression profiles. We performed conventional cytogenetics and immunohistochemical analysis for cytokeratins (CKs) on 126 ccRCCs. Protein expression was evaluated in situ using a semiautomated quantitative system. The results were validated using an independent cohort of 209 ccRCCs with long-term follow-up. Cytogenetic alterations were identified in 96 of 126 ccRCCs, most of them involving chromosome 3 through loss, deletion or translocation. Expression of CKs and E-cadherin in ccRCC was associated with lack of cytogenetic alterations and low nuclear grade. In the validation set, CK7 and CK19 protein expression was associated with better clinical outcome. At the multivariate level, the best model included metastatic status and CK19 expression. Expression microarray analysis on 21 primary ccRCCs and 14 ccRCC metastases identified genes significantly associated with CK7 and CK19 expressing ccRCCs. Two novel ccRCC biomarkers associated with the CK7 positive ccRCC phenotype, PMS2 and MT1-MMP (MMP14), were further validated. We conclude that the variability observed for CK expression in ccRCC can be explained by genetic heterogeneity. Distinct molecular subtypes of ccRCC with prognostic relevance were identified, and the CK7/CK19 expressing subtype is associated with better outcome. Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA. Mertz Kirsten D KD Demichelis Francesca F Sboner Andrea A Hirsch Michelle S MS Cin Paola Dal PD Struckmann Kirsten K Storz Martina M Scherrer Simone S Schmid Daniel M DM Strebel Räto T RT Probst-Hensch Nicole M NM Gerstein Mark M Moch Holger H Rubin Mark A MA eng Journal Article Research Support, Non-U.S. Gov't

United States Int J Cancer 0042124 IM 2008 5 15 9 0 2008 5 15 9 0 ppublish 10.1002/ijc.23565 18478571 rubincancer 18478571 Association of cytokeratin 7 and 19 expression with genomic stability and favorable prognosis in clear cell renal cell cancer. KD Mertz, F Demichelis, A Sboner, MS Hirsch, PD Cin, K Struckmann, M Storz, S Scherrer, DM Schmid, RT Strebel, NM Probst-Hensch, M Gerstein, H Moch, MA Rubin (2008) Int J Cancer 123: 569-76. http://papers.gersteinlab.org/e-print/rubincancer/preprint.pdf 18451266 2008 06 06 2008 06 24

1095-9203 320 5881 2008 Jun 6 Science The transcriptional landscape of the yeast genome defined by RNA sequencing. 1344-9 The identification of untranslated regions, introns, and coding regions within an organism remains challenging. We developed a quantitative sequencing-based method called RNA-Seq for mapping transcribed regions, in which complementary DNA fragments are subjected to high-throughput sequencing and mapped to the genome. We applied RNA-Seq to generate a high-resolution transcriptome map of the yeast genome and demonstrated that most (74.5%) of the nonrepetitive sequence of the yeast genome is transcribed. We confirmed many known and predicted introns and demonstrated that others are not actively used. Alternative initiation codons and upstream open reading frames also were identified for many yeast genes. 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. Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520, USA. Nagalakshmi Ugrappa U Wang Zhong Z Waern Karl K Shou Chong C Raha Debasish D Gerstein Mark M Snyder Michael M eng GEO GSE11209 Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't 2008 05 01

United States Science 0404511 0 Codon, Initiator 0 DNA, Complementary 0 DNA, Intergenic 0 RNA, Fungal 0 Untranslated Regions IM Algorithms Codon, Initiator Computational Biology DNA, Complementary DNA, Intergenic Gene Expression Profiling Genes, Fungal Genome, Fungal Genomics Introns Open Reading Frames RNA, Fungal genetics Saccharomyces cerevisiae genetics Sequence Analysis, RNA Transcription, Genetic Untranslated Regions 2008 5 1 2008 5 3 9 0 2008 6 25 9 0 ppublish 1158441 10.1126/science.1158441 18451266 rnaseq 18451266 The transcriptional landscape of the yeast genome defined by RNA sequencing. U Nagalakshmi, Z Wang, K Waern, C Shou, D Raha, M Gerstein, M Snyder (2008) Science 320: 1344-9. http://papers.gersteinlab.org/e-print/rnaseq/preprint.pdf 18433058 2008 4 24

1097-0134 2008 Apr 23 Proteins HingeMaster: Normal mode hinge prediction approach and integration of complementary predictors. Protein motion is often the link between structure and function and a substantial fraction of proteins move through a domain hinge bending mechanism. Predicting the location of the hinge from a single structure is thus a logical first step towards predicting motion. Here, we describe ways to predict the hinge location by grouping residues with correlated normal-mode motions. We benchmarked our normal-mode based predictor against a gold standard set of carefully annotated hinge locations taken from the Database of Macromolecular Motions. We then compared it with three existing structure-based hinge predictors (TLSMD, StoneHinge, and FlexOracle), plus HingeSeq, a sequence-based hinge predictor. Each of these methods predicts hinges using very different sources of information-normal modes, experimental thermal factors, bond constraint networks, energetics, and sequence, respectively. Thus it is logical that using these algorithms together would improve predictions. 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. (c) 2008 Wiley-Liss, Inc. Department of Physics, Yale University, Bass 432, New Haven, Connecticut 06520. Flores Samuel C SC Keating Kevin S KS Painter Jay J Morcos Faruck F Nguyen Khang K Merritt Ethan A EA Kuhn Leslie A LA Gerstein Mark B MB ENG JOURNAL ARTICLE 2008 4 23

Proteins 8700181 2008 4 25 9 0 2008 4 25 9 0 aheadofprint 10.1002/prot.22060 18433058 hingemaster 18433058 HingeMaster: Normal mode hinge prediction approach and integration of complementary predictors. SC Flores, KS Keating, J Painter, F Morcos, K Nguyen, EA Merritt, LA Kuhn, MB Gerstein (2008) Proteins http://molmovdb.org/cgi-bin/submit-flexoracle.cgi 18414925 2008 05 23

0022-2844 66 5 2008 May J. Mol. Evol. Rapid evolution by positive darwinian selection in T-cell antigen CD4 in primates. 446-56 CD4, an integral membrane glycoprotein, plays a critical role in the immune response and in the life cycle of simian and human immunodeficiency virus (SIV and HIV). Pairwise comparisons of orthologous human and mouse genes show that CD4 is evolving much faster than the majority of mammalian genes. The acceleration is too great to be attributed to a simple relaxation of the action of purifying selection alone. Here we show that the selective pressure acting on CD4 is highly variable between regions in the protein and identify codon sites under strong positive selection. We reconstruct the coding sequences for ancestral primate CD4s and model tertiary structures of all ancestral and extant sequences. Structural mapping of positively selected sites shows they distribute on the surface of the D1 domain of CD4, where the exogenous SIV gp120 protein binds. Moreover, structural models of the ancestral sequences show substantially larger variation in the interfacial electrostatic charge on CD4 and in the surface complementary between CD4 and gp120 in CD4 lineages from primates with natural SIV infections than those without. Thus, positive selection on CD4 among primates may reflect forces driven by SIV infection and could provide a link between changes in sequence and structure of CD4 during evolution and the interaction with the immunodeficiency virus. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA. Zhang Zhengdong D ZD Weinstock George G Gerstein Mark M eng Journal Article 2008 04 15

Germany J Mol Evol 0360051 IM 2007 9 9 2008 2 28 2008 1 16 2008 4 15 2008 4 17 9 0 2008 4 17 9 0 ppublish 10.1007/s00239-008-9097-1 18414925 CD4 Rapid Evolution by Positive Darwinian Selection in T-cell Antigen CD4 in Primates ZD Zhang, G Weinstock, M Gerstein (In press) Journal of Molecular Evolution http://papers.gersteinlab.org/e-print/CD4/preprint.pdf cegs 18414925 18369428 2008 03 28 2008 04 23

1553-7358 4 3 2008 Mar PLoS Comput. Biol. Open access: taking full advantage of the content. e1000037 Bourne Philip E PE Fink J Lynn JL Gerstein Mark M eng Editorial 2008 03 28

United States PLoS Comput Biol 101238922 IM Abstracting and Indexing as Topic methods Authorship Information Dissemination methods Internet Natural Language Processing Periodicals as Topic PubMed Publishing United States 2008 3 29 9 0 2008 4 24 9 0 epublish 10.1371/journal.pcbi.1000037 18369428 killapp 18369428 Open access: taking full advantage of the content. PE Bourne, JL Fink, M Gerstein (2008) PLoS Comput Biol 4: e1000037. http://papers.gersteinlab.org/e-print/killapp/preprint.pdf keck epublishing 18364713 2008 03 26 2008 04 21

1744-4292 4 2008 Mol. Syst. Biol. The role of disorder in interaction networks: a structural analysis. 179 Recent studies have emphasized the value of including structural information into the topological analysis of protein networks. Here, we utilized structural information to investigate the role of intrinsic disorder in these networks. Hub proteins tend to be more disordered than other proteins (i.e. the proteome average); however, we find this only true for those with one or two binding interfaces ('single'-interface hubs). In contrast, the distribution of disordered residues in multi-interface hubs is indistinguishable from the overall proteome. Surprisingly, we find that the binding interfaces in single-interface hubs are highly structured, as is the case for multi-interface hubs. However, the binding partners of single-interface hubs tend to have a higher level of disorder than the proteome average, suggesting that their binding promiscuity is related to the disorder of their binding partners. In turn, the higher level of disorder of single-interface hubs can be partly explained by their tendency to bind to each other in a cascade. 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. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA. Kim Philip M PM Sboner Andrea A Xia Yu Y Gerstein Mark M eng RR19895 RR United States NCRR Journal Article Research Support, N.I.H., Extramural 2008 03 25

England Mol Syst Biol 101235389 0 Saccharomyces cerevisiae Proteins IM Evolution, Molecular Protein Binding Saccharomyces cerevisiae metabolism Saccharomyces cerevisiae Proteins chemistry metabolism Signal Transduction Stochastic Processes 2007 10 15 2008 2 08 2008 3 25 2008 3 28 9 0 2008 4 22 9 0 ppublish msb200816 10.1038/msb.2008.16 18364713 netdisorder 18364713 The role of disorder in interaction networks: a structural analysis. PM Kim, A Sboner, Y Xia, M Gerstein (2008) Mol Syst Biol 4: 179. http://papers.gersteinlab.org/e-print/netdisorder/preprint.pdf proteomicsctr interactions 18328823 2008 04 03

0014-5793 582 8 2008 Apr 9 FEBS Lett. Manually structured digital abstracts: a scaffold for automatic text mining. 1170 Seringhaus Michael M Gerstein Mark M eng Editorial 2008 03 06

Netherlands FEBS Lett 0155157 IM 2008 3 6 2008 3 11 9 0 2008 3 11 9 0 ppublish S0014-5793(08)00192-0 10.1016/j.febslet.2008.02.073 18328823 sdafollowup 18328823 Manually structured digital abstracts: A scaffold for automatic text mining. M Seringhaus, M Gerstein (2008) FEBS Lett 582: 1170. http://papers.gersteinlab.org/e-print/sdafollowup/preprint.pdf keck epublishing 18258921 2008 03 03 2008 04 03

1088-9051 18 3 2008 Mar Genome Res. Systematic evaluation of variability in ChIP-chip experiments using predefined DNA targets. 393-403 The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols, and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Department of Genetics, Stanford University Medical Center, Stanford, California 94305, USA. Johnson David S DS Li Wei W Gordon D Benjamin DB Bhattacharjee Arindam A Curry Bo B Ghosh Jayati J Brizuela Leonardo L Carroll Jason S JS Brown Myles M Flicek Paul P Koch Christoph M CM Dunham Ian I Bieda Mark M Xu Xiaoqin X Farnham Peggy J PJ Kapranov Philipp P Nix David A DA Gingeras Thomas R TR Zhang Xinmin X Holster Heather H Jiang Nan N Green Roland D RD Song Jun S JS McCuine Scott A SA Anton Elizabeth E Nguyen Loan L Trinklein Nathan D ND Ye Zhen Z Ching Keith K Hawkins David D Ren Bing B Scacheri Peter C PC Rozowsky Joel J Karpikov Alexander A Euskirchen Ghia G Weissman Sherman S Gerstein Mark M Snyder Michael M Yang Annie A Moqtaderi Zarmik Z Hirsch Heather H Shulha Hennady P HP Fu Yutao Y Weng Zhiping Z Struhl Kevin K Myers Richard M RM Lieb Jason D JD Liu X Shirley XS eng GEO GSE10114 1R01 HG004069-01 HG United States NHGRI Evaluation Studies Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't 2008 02 07

United States Genome Res 9518021 0 Oligonucleotide Probes 9007-49-2 DNA IM Algorithms Chromatin Immunoprecipitation methods Chromosome Aberrations DNA chemistry Genome, Human Humans Oligonucleotide Array Sequence Analysis methods Oligonucleotide Probes Polymerase Chain Reaction ROC Curve Reproducibility of Results Tandem Repeat Sequences 2008 2 7 2008 2 9 9 0 2008 4 4 9 0 ppublish gr.7080508 10.1101/gr.7080508 18258921 encodespikein 18258921 Systematic evaluation of variability in ChIP-chip experiments using predefined DNA targets. DS Johnson, W Li, DB Gordon, A Bhattacharjee, B Curry, J Ghosh, L Brizuela, JS Carroll, M Brown, P Flicek, CM Koch, I Dunham, M Bieda, X Xu, PJ Farnham, P Kapranov, DA Nix, TR Gingeras, X Zhang, H Holster, N Jiang, R Green, JS Song, SA McCuine, E Anton, L Nguyen, ND Trinklein, Z Ye, K Ching, D Hawkins, B Ren, PC Scacheri, J Rozowsky, A Karpikov, G Euskirchen, S Weissman, M Gerstein, M Snyder, A Yang, Z Moqtaderi, H Hirsch, HP Shulha, Y Fu, Z Weng, K Struhl, RM Myers, JD Lieb, XS Liu (2008) Genome Res http://papers.gersteinlab.org/e-print/encodespikein/preprint.pdf encode 18254929 2008 2 7

1465-6914 9 1 2008 Jan 31 Genome Biol. Uncovering trends in gene naming. 401 ABSTRACT: We take stock of current genetic nomenclature and attempt to organize strange and notable gene names. 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. Program in Computational Biology and Bioinformatics, Yale University, Whitney Avenue, New Haven, CT 06520, USA. mark.gerstein@yale.edu. Seringhaus Michael R MR Cayting Philip D PD Gerstein Mark B MB ENG JOURNAL ARTICLE 2008 1 31

Genome Biol 100960660 2008 1 31 2008 2 8 9 0 2008 2 8 9 0 aheadofprint gb-2008-9-1-401 10.1186/gb-2008-9-1-401 18254929 funnygene 18254929 Uncovering trends in gene naming. MR Seringhaus, PD Cayting, MB Gerstein (2008) Genome Biol 9: 401. http://papers.gersteinlab.org/e-print/funnygene/preprint.pdf keck epublishing http://www.gersteinlab.org/proj/funnygene/ 18173853 2008 1 28

1465-6914 9 1 2008 Jan 3 Genome Biol. Systematic analysis of transcribed loci in ENCODE regions using RACE sequencing reveals extensive transcription in the human genome. R3 ABSTRACT: BACKGROUND: Recent studies of the mammalian transcriptome have revealed a large number of additional transcribed regions and extraordinary complexity in transcript diversity. 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. RESULTS: We have interrogated the transcribed loci in 420 selected ENCyclopedia Of DNA Elements (ENCODE) regions using rapid amplification of cDNA ends (RACE) sequencing. We analyzed annotated known gene regions, but primarily we focused on novel transcriptionally active regions (TARs), which were previously identified by high-density oligonucleotide tiling arrays and on random regions that were not believed to be transcribed. We found RACE sequencing to be very sensitive and were able to detect low levels of transcripts in specific cell types that were not detectable by microarrays. We also observed many instances of sense-antisense transcripts; further analysis suggests that many of the antisense transcripts (but not all) may be artifacts generated from the reverse transcription reaction. Our results show that the majority of the novel TARs analyzed (60%) are connected to other novel TARs or known exons. Of previously unannotated random regions, 17% were shown to produce overlapping transcripts. Furthermore, it is estimated that 9% of the novel transcripts encode proteins. CONCLUSION: We conclude that RACE sequencing is an efficient, sensitive, and highly accurate method for characterization of the transcriptome of specific cell/tissue types. Using this method, it appears that much of the genome is represented in polyA+ RNA. Moreover, a fraction of the novel RNAs can encode protein and are likely to be functional. Molecular, Cellular and Developmental Biology Department, KBT918, Yale University, 266 Whitney Avenue, New Haven, Connecticut 06511, USA. Michael.Snyder@yale.edu. Wu Jia Qian JQ Du Jiang J Rozowsky Joel J Zhang Zhengdong Z Urban Alexander E AE Euskirchen Ghia G Weissman Sherman S Gerstein Mark M Snyder Michael M ENG JOURNAL ARTICLE 2008 1 03

Genome Biol 100960660 2007 11 7 2007 12 6 2008 1 3 2008 1 03 2008 1 5 9 0 2008 1 5 9 0 aheadofprint gb-2008-9-1-r3 10.1186/gb-2008-9-1-r3 18173853 encoderaceseq 18173853 Systematic analysis of transcribed loci in ENCODE regions using RACE sequencing reveals extensive transcription in the human genome. JQ Wu, J Du, J Rozowsky, Z Zhang, AE Urban, G Euskirchen, S Weissman, M Gerstein, M Snyder (2008) Genome Biol 9: R3 http://papers.gersteinlab.org/e-print/encoderaceseq/preprint.pdf encode 18077332 2007 12 20 2008 01 28

1091-6490 104 51 2007 Dec 18 Proc. Natl. Acad. Sci. U.S.A. Positive selection at the protein network periphery: evaluation in terms of structural constraints and cellular context. 20274-9 Because of recent advances in genotyping and sequencing, human genetic variation and adaptive evolution in the primate lineage have become major research foci. Here, we examine the relationship between genetic signatures of adaptive evolution and network topology. We find a striking tendency of proteins that have been under positive selection (as compared with the chimpanzee) to be located at the periphery of the interaction network. Our results are based on the analysis of two types of genome evolution, both in terms of intra- and interspecies variation. First, we looked at single-nucleotide polymorphisms and their fixed variants, single-nucleotide differences in the human genome relative to the chimpanzee. Second, we examine fixed structural variants, specifically large segmental duplications and their polymorphic precursors known as copy number variants. We propose two complementary mechanisms that lead to the observed trends. First, we can rationalize them in terms of constraints imposed by protein structure: We find that positively selected sites are preferentially located on the exposed surface of proteins. Because central network proteins (hubs) are likely to have a larger fraction of their surface involved in interactions, they tend to be constrained and under negative selection. Conversely, we show that the interaction network roughly maps to cellular organization, with the periphery of the network corresponding to the cellular periphery (i.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. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA. pmkim@alum.mit.edu Kim Philip M PM Korbel Jan O JO Gerstein Mark B MB eng Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't 2007 12 12

United States Proc Natl Acad Sci U S A 7505876 0 Proteins IM Adaptation, Biological genetics Animals Evolution, Molecular Gene Dosage Genome Genome, Human genetics Humans Mutation Polymorphism, Single Nucleotide Protein Conformation Proteins genetics metabolism Selection (Genetics) 2007 12 12 2007 12 14 9 0 2008 1 29 9 0 ppublish 0710183104 10.1073/pnas.0710183104 18077332 netpossel 18077332 Positive selection at the protein network periphery: Evaluation in terms of structural constraints and cellular context. PM Kim, JO Korbel, MB Gerstein (2007) Proc Natl Acad Sci U S A. cegs 2007-summary,interactions http://www.gersteinlab.org/proj/netpossel/ http://papers.gersteinlab.org/e-print/netpossel/preprint.pdf 18065488 2008 01 21

1537-1719 25 1 2008 Jan Mol. Biol. Evol. Analysis of nuclear receptor pseudogenes in vertebrates: how the silent tell their stories. 131-43 Transcription factor pseudogenes have not been systematically studied before. Nuclear receptors (NRs) constitute one of the largest groups of transcription factors in animals (e.g., 48 NRs in human). The availability of whole-genome sequences enables a global inventory of the NR pseudogenes in a number of vertebrate model organisms. Here we identify the NR pseudogenes in 8 vertebrate organisms and make our results available online at http://www.pseudogene.org/nr. The assignments reveal that NR pseudogenes as a group have characteristics related to generation and distribution contrary to expectations derived from previous large-scale pseudogene studies. In particular, 1) despite its large size, the NR gene family has only a very small number of pseudogenes in each of the vertebrate genomes examined; 2) despite the low transcription levels of NR genes, except for one, all other NR pseudogenes identified in this study are retropseudogenes; and 3) no duplicated NR pseudogenes are found, contrary to the fact that the NR gene family was expanded through several waves of gene duplication events. Our analyses further reveal a number of interesting aspects of NR pseudogenes. Specifically, through careful sequence analysis, we identify remnant introns in 2 mouse retropseudogenes, psiRev-erbbeta and psiLRH1. Generated from partially processed pre-mRNAs, they appear to be rare examples of highly unusual "semiprocessed" pseudogenes. Second, by comparing the genomic sequences, we uncover a pseudogene that is unique to the human lineage relative to chimpanzee. Generated by a recent duplication of a segment in the human genome, this pseudogene is a "duplicated-processed" pseudogene, belonging to a new pseudogene species. Finally, FXRbeta was nonfunctionalized in the human lineage and thus appears to be an example of a rare unitary pseudogene. By comparing orthologous sequences, we dated the FXR-FXRbeta duplication and the nonfunctionalization of FXRbeta in primates. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA. Zhang Zhengdong D ZD Cayting Philip P Weinstock George G Gerstein Mark M eng T15 LM07056 LM United States NLM Journal Article Research Support, N.I.H., Extramural 2007 12 07

United States Mol Biol Evol 8501455 IM 2007 12 7 2007 12 11 9 0 2007 12 11 9 0 ppublish msm251 10.1093/molbev/msm251 18065488 nr-pseudogenes Analysis of nuclear receptor pseudogenes in vertebrates: How the silent tell their stories ZD Zhang, P Cayting, G Weinstock, M Gerstein (In press) Molecular Biology and Evolution http://papers.gersteinlab.org/e-print/nr-pseudogenes/preprint.pdf pseudogenes http://pseudogene.org/nr/ 18065488 18056067 2008 01 15 2008 02 05

1460-2059 24 2 2008 Jan 15 Bioinformatics An integrated system for studying residue coevolution in proteins. 290-2 Residue coevolution has recently emerged as an important concept, especially in the context of protein structures. While a multitude of different functions for quantifying it have been proposed, not much is known about their relative strengths and weaknesses. Also, subtle algorithmic details have discouraged implementing and comparing them. We addressed this issue by developing an integrated online system that enables comparative analyses with a comprehensive set of commonly used scoring functions, including Statistical Coupling Analysis (SCA), Explicit Likelihood of Subset Variation (ELSC), mutual information and correlation-based methods. A set of data preprocessing options are provided for improving the sensitivity and specificity of coevolution signal detection, including sequence weighting, residue grouping and the filtering of sequences, sites and site pairs. A total of more than 100 scoring variations are available. The system also provides facilities for studying the relationship between coevolution scores and inter-residue distances from a crystal structure if provided, which may help in understanding protein structures. AVAILABILITY: The system is available at http://coevolution.gersteinlab.org. The source code and JavaDoc API can also be downloaded from t