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Genome-scale community modeling for deciphering the inter-microbial metabolic interactions in fungus-farming termite gut microbiome.
Comput Biol Med
March 2023
School of Energy Science and Engineering, Indian Institute of Technology Kharagpur, West Bengal, 721302, India; P.K. Sinha Centre for Bioenergy and Renewables, Indian Institute of Technology Kharagpur, West Bengal, 721302, India. Electronic address:
Specialized microbial communities in the fungus-farming termite gut and fungal comb microbiome help maintain host nutrition through interactive biochemical activities of complex carbohydrate degradation. Numerous research studies have been focused on identifying the microbial species in the termite gut and fungal comb microbiota, but the community-wide metabolic interaction patterns remain obscure. The inter-microbial metabolic interactions in the community environment are essential for executing biochemical processes like complex carbohydrate degradation and maintaining the host's physicochemical homeostasis.
View Article and Find Full Text PDFStanDep: Capturing transcriptomic variability improves context-specific metabolic models.
PLoS Comput Biol
May 2020
Department of Pediatrics, University of California, San Diego, School of Medicine, La Jolla, CA, United States of America.
Diverse algorithms can integrate transcriptomics with genome-scale metabolic models (GEMs) to build context-specific metabolic models. These algorithms require identification of a list of high confidence (core) reactions from transcriptomics, but parameters related to identification of core reactions, such as thresholding of expression profiles, can significantly change model content. Importantly, current thresholding approaches are burdened with setting singular arbitrary thresholds for all genes; thus, resulting in removal of enzymes needed in small amounts and even many housekeeping genes.
View Article and Find Full Text PDFMaximal sum of metabolic exchange fluxes outperforms biomass yield as a predictor of growth rate of microorganisms.
PLoS One
August 2015
School of Computer Sciences, and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
Growth rate has long been considered one of the most valuable phenotypes that can be measured in cells. Aside from being highly accessible and informative in laboratory cultures, maximal growth rate is often a prime determinant of cellular fitness, and predicting phenotypes that underlie fitness is key to both understanding and manipulating life. Despite this, current methods for predicting microbial fitness typically focus on yields [e.
View Article and Find Full Text PDFAdapting a Clinical Data Repository to ICD-10-CM through the use of a Terminology Repository.
AMIA Annu Symp Proc
August 2015
Laboratory for Informatics Development, NIH Clinical Center, Bethesda, MD.
Clinical data repositories frequently contain patient diagnoses coded with the International Classification of Diseases, Ninth Revision (ICD-9-CM). These repositories now need to accommodate data coded with the Tenth Revision (ICD-10-CM). Database users wish to retrieve relevant data regardless of the system by which they are coded.
View Article and Find Full Text PDFA genetic algorithm with conformational memories for structure prediction of polypeptides.
J Biomol Struct Dyn
August 2003
Centro de Ciencias Físicas, Universidad Nacional Autónoma de México, Apdo. Postal 48-3, 62250 Cuernavaca, Morelos, México.
We have developed an iterative hybrid algorithm (HA) to predict the 3D structure of peptides starting from their amino acid sequence. The HA is made of a modified genetic algorithm (GA) coupled to a local optimizer. Each HA iteration is carried out in two phases.
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