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Biodata Management and Analysis Study Section [BDMA]

The Biodata Management and Analysis (BDMA) study section reviews grant applications concerned with computational methods for acquisition, management, querying, sharing and analysis of biological data. Areas of interest overlap with basic research in computer science, statistics, mathematics, computational biology and bioinformatics. Within this context, hypothesis-driven applications and applications integrated with experimentation are also welcomed.

Rosters

Topics

  • Methods for data acquisition, storage, management, query and representation, data integrity and validation, and data integration.
  • Methods for the analysis of large datasets from high throughput experiments including genomic, transcriptomic, nucleic acid:protein crosslinking-immunoprecipitation, proteomic and metabolomic studies.
  • Methods for pattern discovery, gene network inference, biomarker identification, protein and nucleic acid structure prediction, drug discovery and re-use.
  • Scientific visualization systems for the summary, integration, and representation of data.
  • Design and engineering of computing hardware and software systems for biological research involving but not limited to ‘omics, medical and cellular imaging, electronic medical records and biological simulations.
Shared Interests
  • There are shared interests with GCAT with regard to the computational analysis of –omics data. Applications that propose computational methods and tools for improving ‘-omic data analysis and integration may be assigned in BDMA. Applications developing such methods with a focus on fundamental biological questions with regard to genomic structure or expression networks may be assigned to GCAT
  • There are shared interests with BCHI with regard to data mining of electronic medical records or integration of these records with other data sources. Applications that are developing new or improving the performance of existing computational strategies for mining and integrating electronic health records with ‘omics or imaging data can be assigned to BDMA.Applications that focus on new mining and integration methods and representing data for clinical decision support may be assigned to BCHI.
  • There are shared interests with BMRD with regard to statistical analysis of genomic and gene expression data. Applications that focus on the development and maintenance of existing research software in this domain may be assigned to BDMA. Applications that focus on developing new methods of genomic and gene expression data and statistical genetic studies may be assigned to BMRD.
  • There are shared interests with MABS, in particular with systems biology research. Applications that focus on the improving or developing new algorithms or computational tools for general problems in network inference can be assigned in BDMA. Applications that have a specific biological focus can be assigned to MABS.
  • There are shared interests with MSFD with regard to developing computational approaches for protein and nucleic acid structure prediction. Applications that focus on informatics approaches, developing databases, or extending existing software tools be assigned to BDMA. Applications that develop new methods for modeling molecular structures can be assigned to MSFD.
  • There are shared interests with imaging SRGs. Applications that focus on the maintenance or integration of existing software tools can be assigned to BDMA. Applications that develop new data analysis methods and tools could be assigned to the relevant imaging SRG (e.g. NOIT, BMIT-A, BMIT-B, MEDI, EBIT).

Closely Related

  

Keywords: computational biology, bioinformatics, algorithm development, machine learning, natural language processing, ontologies, statistics, database, data processing, data analysis, data integration, data mining, genomics, transcriptomics, proteomics, metabolomics, data visualization, graph theory, computational speedup, software engineering, computer hardware engineering, “big data