Literature DB >> 32877338

Functional Genomics Platform, A Cloud-Based Platform for Studying Microbial Life at Scale.

Edward E Seabolt, Gowri Nayar, Harsha Krishnareddy, Akshay Agarwal, Kristen L Beck, Ignacio Terrizzano, Eser Kandogan, Mark Kunitomi, Mary Roth, Vandana Mukherjee, James H Kaufman.   

Abstract

The rapid growth in biological sequence data is revolutionizing our understanding of genotypic diversity and challenging conventional approaches to informatics. With the increasing availability of genomic data, traditional bioinformatic tools require substantial computational time and the creation of ever-larger indices each time a researcher seeks to gain insight from the data. To address these challenges, we pre-computed important relationships between biological entities spanning the Central Dogma of Molecular Biology and captured this information in a relational database. The database can be queried across hundreds of millions of entities and returns results in a fraction of the time required by traditional methods. In this paper, we describe Functional Genomics Platform (formerly known as OMXWare), a comprehensive database relating genotype to phenotype for bacterial life. Continually updated, the Functional Genomics Platform today contains data derived from 200,000 curated, self-consistently assembled genomes. The database stores functional data for over 68 million genes, 52 million proteins, and 239 million domains with associated biological activity annotations from Gene Ontology, KEGG, MetaCyc, and Reactome. The Functional Genomics Platform maps all of the many-to-many connections between each biological entity including the originating genome, gene, protein, and protein domain. Various microbial studies, from infectious disease to environmental health, can benefit from the rich data and connections. We describe the data selection, the pipeline to create and update the Functional Genomics Platform, and the developer tools (Python SDK and REST APIs)which allow researchers to efficiently study microbial life at scale.

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Year:  2022        PMID: 32877338     DOI: 10.1109/TCBB.2020.3021231

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  5 in total

1.  Semi-Supervised Pipeline for Autonomous Annotation of SARS-CoV-2 Genomes.

Authors:  Kristen L Beck; Edward Seabolt; Akshay Agarwal; Gowri Nayar; Simone Bianco; Harsha Krishnareddy; Timothy A Ngo; Mark Kunitomi; Vandana Mukherjee; James H Kaufman
Journal:  Viruses       Date:  2021-12-03       Impact factor: 5.048

2.  Functional profiling of COVID-19 respiratory tract microbiomes.

Authors:  Niina Haiminen; Filippo Utro; Ed Seabolt; Laxmi Parida
Journal:  Sci Rep       Date:  2021-03-19       Impact factor: 4.379

3.  Re-purposing software for functional characterization of the microbiome.

Authors:  Laura-Jayne Gardiner; Niina Haiminen; Filippo Utro; Laxmi Parida; Ed Seabolt; Ritesh Krishna; James H Kaufman
Journal:  Microbiome       Date:  2021-01-09       Impact factor: 14.650

4.  Analysis and forecasting of global real time RT-PCR primers and probes for SARS-CoV-2.

Authors:  Gowri Nayar; Edward E Seabolt; Mark Kunitomi; Akshay Agarwal; Kristen L Beck; Vandana Mukherjee; James H Kaufman
Journal:  Sci Rep       Date:  2021-04-26       Impact factor: 4.379

5.  Predicting Epitope Candidates for SARS-CoV-2.

Authors:  Akshay Agarwal; Kristen L Beck; Sara Capponi; Mark Kunitomi; Gowri Nayar; Edward Seabolt; Gandhar Mahadeshwar; Simone Bianco; Vandana Mukherjee; James H Kaufman
Journal:  Viruses       Date:  2022-08-21       Impact factor: 5.818

  5 in total

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