David J Reiss

Summary

Affiliation: Institute for Systems Biology
Country: USA

Publications

  1. pmc CTCF physically links cohesin to chromatin
    Eric D Rubio
    Department of Radiation Oncology, University of Washington School of Medicine, Seattle WA 98195, USA
    Proc Natl Acad Sci U S A 105:8309-14. 2008
  2. pmc The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo
    Richard Bonneau
    New York University, Biology Department, Center for Comparative Functional Genomics, New York, NY 10003, USA
    Genome Biol 7:R36. 2006
  3. pmc Multi-species integrative biclustering
    Peter Waltman
    Computer Science Department, Warren Weaver Hall Room 305, 251 Mercer Street, New York, NY 10012, USA
    Genome Biol 11:R96. 2010
  4. ncbi request reprint Predicting protein-peptide interactions via a network-based motif sampler
    David J Reiss
    Institute for Systems Biology, Seattle, WA 98103 8904, USA
    Bioinformatics 20:i274-82. 2004
  5. pmc Tools enabling the elucidation of molecular pathways active in human disease: application to Hepatitis C virus infection
    David J Reiss
    Institute for Systems Biology, 1441 N, 34th Street, Seattle, WA 98103, USA
    BMC Bioinformatics 6:154. 2005
  6. pmc Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks
    David J Reiss
    Institute for Systems Biology, 1441 N, 34th St, Seattle, WA 98103 8904, USA
    BMC Bioinformatics 7:280. 2006
  7. ncbi request reprint Model-based deconvolution of genome-wide DNA binding
    David J Reiss
    Institute for Systems Biology, 1441 N 34th St Seattle, WA 98103 8904, USA
    Bioinformatics 24:396-403. 2008
  8. pmc Large scale physiological readjustment during growth enables rapid, comprehensive and inexpensive systems analysis
    Marc T Facciotti
    Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA
    BMC Syst Biol 4:64. 2010
  9. pmc Coordination of frontline defense mechanisms under severe oxidative stress
    Amardeep Kaur
    Institute for Systems Biology, Seattle, WA 98103, USA
    Mol Syst Biol 6:393. 2010
  10. pmc Prevalence of transcription promoters within archaeal operons and coding sequences
    Tie Koide
    Institute for Systems Biology, Seattle, WA 98103, USA
    Mol Syst Biol 5:285. 2009

Collaborators

Detail Information

Publications25

  1. pmc CTCF physically links cohesin to chromatin
    Eric D Rubio
    Department of Radiation Oncology, University of Washington School of Medicine, Seattle WA 98195, USA
    Proc Natl Acad Sci U S A 105:8309-14. 2008
    ..These results have implications for the functional role of cohesin subunits in the pathogenesis of Cornelia de Lange syndrome and Roberts syndromes...
  2. pmc The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo
    Richard Bonneau
    New York University, Biology Department, Center for Comparative Functional Genomics, New York, NY 10003, USA
    Genome Biol 7:R36. 2006
    ..Several specific regulatory predictions were experimentally tested and verified...
  3. pmc Multi-species integrative biclustering
    Peter Waltman
    Computer Science Department, Warren Weaver Hall Room 305, 251 Mercer Street, New York, NY 10012, USA
    Genome Biol 11:R96. 2010
    ....
  4. ncbi request reprint Predicting protein-peptide interactions via a network-based motif sampler
    David J Reiss
    Institute for Systems Biology, Seattle, WA 98103 8904, USA
    Bioinformatics 20:i274-82. 2004
    ..Such a question was recently posed by the use of random peptide screens to characterize the ligands of one such PRM, the SH3 domain...
  5. pmc Tools enabling the elucidation of molecular pathways active in human disease: application to Hepatitis C virus infection
    David J Reiss
    Institute for Systems Biology, 1441 N, 34th Street, Seattle, WA 98103, USA
    BMC Bioinformatics 6:154. 2005
    ....
  6. pmc Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks
    David J Reiss
    Institute for Systems Biology, 1441 N, 34th St, Seattle, WA 98103 8904, USA
    BMC Bioinformatics 7:280. 2006
    ..In organisms where these motifs are not known, their de novo detection, integrated into the clustering algorithm, can help to guide the process towards more biologically parsimonious solutions...
  7. ncbi request reprint Model-based deconvolution of genome-wide DNA binding
    David J Reiss
    Institute for Systems Biology, 1441 N 34th St Seattle, WA 98103 8904, USA
    Bioinformatics 24:396-403. 2008
    ....
  8. pmc Large scale physiological readjustment during growth enables rapid, comprehensive and inexpensive systems analysis
    Marc T Facciotti
    Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA
    BMC Syst Biol 4:64. 2010
    ..Therefore, a relatively quick and inexpensive strategy for observing changes in large fractions of the genetic elements is highly desirable...
  9. pmc Coordination of frontline defense mechanisms under severe oxidative stress
    Amardeep Kaur
    Institute for Systems Biology, Seattle, WA 98103, USA
    Mol Syst Biol 6:393. 2010
    ....
  10. pmc Prevalence of transcription promoters within archaeal operons and coding sequences
    Tie Koide
    Institute for Systems Biology, Seattle, WA 98103, USA
    Mol Syst Biol 5:285. 2009
    ..Using experimental validation, we illustrate the prevalence of overlapping genomic signals in archaeal transcription, casting doubt on the general perception of rigid boundaries between coding sequences and regulatory elements...
  11. pmc A single transcription factor regulates evolutionarily diverse but functionally linked metabolic pathways in response to nutrient availability
    Amy K Schmid
    Institute for Systems Biology, Seattle, WA 98103 8904, USA
    Mol Syst Biol 5:282. 2009
    ..Simultaneous analysis of metabolic and gene regulatory network architectures suggests an ongoing process of co-evolution in which TrmB integrates the expression of metabolic enzyme-coding genes of diverse origins...
  12. pmc Network portal: a database for storage, analysis and visualization of biological networks
    Serdar Turkarslan
    Institute for Systems Biology, Seattle, WA 98109, USA and Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
    Nucleic Acids Res 42:D184-90. 2014
    ..The modular architecture, simple data formats and open API support community development of the portal. ..
  13. pmc The anatomy of microbial cell state transitions in response to oxygen
    Amy K Schmid
    Institute for Systems Biology, Seattle, Washington 98103, USA
    Genome Res 17:1399-413. 2007
    ..Dynamic temporal analysis of relationships between transcription and translation of key genes suggests several important mechanisms for cellular sustenance under anoxia as well as specific instances of post-transcriptional regulation...
  14. pmc A systems level predictive model for global gene regulation of methanogenesis in a hydrogenotrophic methanogen
    Sung Ho Yoon
    Institute for Systems Biology, Seattle, Washington 98109, USA
    Genome Res 23:1839-51. 2013
    ..The EGRIN model demonstrates regulatory affiliations within methanogenesis as well as between methanogenesis and other cellular functions. ..
  15. pmc Parallel evolution of transcriptome architecture during genome reorganization
    Sung Ho Yoon
    Institute for Systems Biology, Seattle, Washington 98109, USA
    Genome Res 21:1892-904. 2011
    ..Importantly, our integrated analysis has revealed that organisms adapted to higher growth temperatures have lower tolerance for genome reorganization events that disrupt operon structures...
  16. pmc Integration and visualization of systems biology data in context of the genome
    J Christopher Bare
    Institute for Systems Biology, 1441 N 34th Street, Seattle, WA 98103, USA
    BMC Bioinformatics 11:382. 2010
    ..Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment...
  17. pmc Halobacterium salinarum NRC-1 PeptideAtlas: toward strategies for targeted proteomics and improved proteome coverage
    Phu T Van
    Institute for Systems Biology, 1441 North 34th Street, Seattle, Washington 98103, USA
    J Proteome Res 7:3755-64. 2008
    ..Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics...
  18. pmc General transcription factor specified global gene regulation in archaea
    Marc T Facciotti
    Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98121, USA
    Proc Natl Acad Sci U S A 104:4630-5. 2007
    ....
  19. pmc Niche adaptation by expansion and reprogramming of general transcription factors
    Serdar Turkarslan
    Baliga Lab, Institute for Systems Biology, Seattle, WA 98109, USA
    Mol Syst Biol 7:554. 2011
    ..Based on these insights, we have introduced a synthetically redesigned TFB and altered the regulation of existing TFBs to illustrate how archaea can rapidly generate novel phenotypes by simply reprogramming their TFB regulatory network...
  20. pmc The Gaggle: an open-source software system for integrating bioinformatics software and data sources
    Paul T Shannon
    Institute for Systems Biology, Seattle, WA 98103, USA
    BMC Bioinformatics 7:176. 2006
    ..A solution to this problem should recognize that data types, formats and software in this high throughput age of biology are constantly changing...
  21. pmc An integrated systems approach for understanding cellular responses to gamma radiation
    Kenia Whitehead
    Institute for Systems Biology, Seattle, WA 98103 8904, USA
    Mol Syst Biol 2:47. 2006
    ....
  22. pmc Molecular mechanisms of system responses to novel stimuli are predictable from public data
    Samuel A Danziger
    Seattle Biomedical Research Institute, Seattle, WA 98109 5219 USA, Institute for Systems Biology, Seattle, WA 98109 5240 USA, The Key Laboratory of Developmental Genes and Human Disease, Ministry of Education, Institute of Life Science, Southeast University, Nanjing 210096, China and Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 704, Taiwan
    Nucleic Acids Res 42:1442-60. 2014
    ....
  23. pmc Global analysis of mRNA stability in Mycobacterium tuberculosis
    Tige R Rustad
    Seattle Biomedical Research Institute, 307 Westlake Avenue North, Seattle, WA 98109, USA
    Nucleic Acids Res 41:509-17. 2013
    ..The generally stable transcriptome described here, and the additional stabilization in response to physiologically relevant stresses, has far-ranging implications for how this pathogen is able to adapt in its human host...
  24. ncbi request reprint BioNetBuilder: automatic integration of biological networks
    Iliana Avila-Campillo
    Department of Biology, New York University, New York, NY, USA
    Bioinformatics 23:392-3. 2007
    ..The BioNetBuilder plugin client is available as a Java Webstart, providing a platform-independent network interface to these public databases. Availability: http://err.bio.nyu.edu/cytoscape/bionetbuilder/..
  25. ncbi request reprint A predictive model for transcriptional control of physiology in a free living cell
    Richard Bonneau
    Center for Genomics and Systems Biology, New York University, New York, NY 10003, USA Courant Institute of Mathematical Sciences, Department of Computer Science, New York University, New York, NY 10003, USA
    Cell 131:1354-65. 2007
    ..This study supports the claim that the high degree of connectivity within biological and EF networks will enable the construction of similar models for any organism from relatively modest numbers of experiments...