Berkeley Lab

Computation

ComputationENIGMA’s Computation component is tasked with data management analysis and dissemination for the ENIGMA Scientific Focus Area.

The goal is to extract meaningful and statistically significant patterns from large and complex datasets by distinguishing signal from noise and integrating evidence across different data types. To this end, members of the group are developing and maintaining widely used computational tools, including the MicrobesOnline, RegTransBase, and RegPrecise databases, plus data integration and visualization tools, such as Gaggle, that support a wide external user base.

Analytical efforts in the ENIGMA Computation component are focused on regulatory network predictions and inferences, gene functional annotation, and statistical approaches for environmental genomics. These efforts are integrated with all of the projects in ENIGMA. In addition to developing algorithms to find patterns within such noisy biological data as transcriptome structure, peptide atlas, protein-DNA interactions, and biodiversity from NextGen sequencing data, members of the ENIGMA Computation component are integrating diverse data types for the study of modular microbial architectures across scales, such as community assemblages and regulons – groups of genes regulated by the same protein. They are performing similar tasks for the study of microbial community networks, genetic regulatory networks, and other genetic and environmental influences that encode dynamical interrelationships across these modules.

 

Computation & Knowledgebase Team

  • Alm, Eric
    Alm, Eric
    Deputy Director, Computation ejalm@mit.edu
  • BALIGA, NITIN
    Baliga, Nitin
    Director, Computation nbaliga@systemsbiology.org (206) 732-1266
  • CHANDONIA,-JOHN-MARC
    Chandonia, John-Marc
    Principal Investigator jmchandonia@lbl.gov (510) 292-9495
  • DvH_MM_PopulationCurves_Turkarslan2
    ENIGMA Researchers Uncover Factors in Microbial...
    Serdar Turkarslan, a Senior Research Scientist at the Institute for Systems...
  • Metabolizing Data in the Cloud
    ENIGMA researchers at Scripps Research Institute have developed tools with available...
  • Stable protein interactome of the model sulfate reducing bacterium Desulfovibrio vulgaris Hildenborough
    Stable protein interactome of the model...
    Combined (AP-MS + tagless) interactome for D. vulgaris
  • Smith_Rocha1
    Bacterial Communities As Precise Biosensors Of...
    ENIGMA scientists show that DNA from natural bacterial communities can be...