Global Scale Metabolic Pathway Reconstruction From Environmental Genomes
For more than 3.5 billion years, microorganisms have been the dominant form of life on Earth, mediating global fluxes of matter and energy. Over the past decade, high-throughput sequencing and mass spectrometry platforms generating multi-omic sequence information (DNA, RNA, protein and metabolites) which contain information about the function and identity of microbial life, have transformed our perception of this microcosmos, illuminating microbial dark matter and conceptually linking microorganisms at the individual, population, and community levels to a wide range of ecosystem functions and services. Despite the power and promise of this new perception, a persistent paucity of scalable software tools to mine, monitor, and interact with environmental sequence information limits knowledge creation and translation. This is especially vexing in a time of climate change when microbial community metabolism offers a virtual blueprint to rebuild our global future in more sustainable ways. EngCyc is the next step in overcoming this challenge.
EngCyc provides direct and comparative access to virtual blueprints of microbial community metabolism through a portal system on the World Wide Web and support user-defined blueprint construction using MetaPathways 3.0. EngCyc and the associated software enables gene and pathway discovery. Downstream analysis modules provide intuitive and beautiful data exploration options to power knowledge creation and translation.
Publications
Research Team
Steven manages and guides scientific exploration.
Aria is passionate about the application of high performance data analytics and believes that combined with intelligent statistical and computational technologies, data hold the answers to many burgeoning questions facing multiple industries today. At EngCyc she oversees the technical planning and team.
Kishori M. Konwar is a Computational Biologist at the Broad Institute of MIT and Harvard where he develops distributed algorithms for large-scale biological problems. His past appointments have been at the MIT Computer Science & Artificial Intelligence Lab (CSAIL) and at the Department of Microbiology at the University of British Columbia. He has many interests including computational biology, marketing, engineering, business intelligence, finance, or any fields that are being transformed by the advent of large-scale data.
Ryan designs and executes purpose-made software solutions for exploring complex biological systems.
Connor develops software for the analysis of microbiome sequence information. He specializes in genome annotation, microbial ecology, and evolution.
Tomer is a Senior Bioinformaticist at Altman Analytics LLC and the Information Architect for the BCB2 Project. He is interested in applying bioinformatics, computer modeling, and machine learning to better understand microbiomes.
Julia is responsible for aggregating multi-omics datasets for the EngCyc project, testing software, and editing the MetaPathways manual. She specializes in analysing single-cell and metagenomic datasets.
Aditi is working on building microbial metabolic models using pathway/genome databases for anaerobic and aerobic wastewater treatment processes.
Tony is exploring methods to increase the completeness of metabolic models by leveraging protein structure prediction.
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