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Kalyan C. Vinnakota

dblp:217/2262 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2018
0000-0003-2185-2213ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › systems biology
biochemical simulation
0.112009
BISEN: Biochemical Simulation Environment · Bioinform. 2009
Bioinformatics and computational biology › systems biology › computational systems biology
systems biology modeling
0.112009
BISEN: Biochemical Simulation Environment · Bioinform. 2009

Methods — techniques the papers use, named apart from their topics

thermodynamic modeling · 0.1differential equation generation · 0.1
YearPublicationVenuePosition
2018 Systems-level computational modeling demonstrates fuel selection switching in high capacity running and low capacity running rats
abstract
High capacity and low capacity running rats, HCR and LCR respectively, have been bred to represent two extremes of running endurance and have recently demonstrated disparities in fuel usage during transient aerobic exercise. HCR rats can maintain fatty acid (FA) utilization throughout the course of transient aerobic exercise whereas LCR rats rely predominantly on glucose utilization. We hypothesized that the difference between HCR and LCR fuel utilization could be explained by a difference in mitochondrial density. To test this hypothesis and to investigate mechanisms of fuel selection, we used a constraint-based kinetic analysis of whole-body metabolism to analyze transient exercise data from these rats. Our model analysis used a thermodynamically constrained kinetic framework that accounts for glycolysis, the TCA cycle, and mitochondrial FA transport and oxidation. The model can effectively match the observed relative rates of oxidation of glucose versus FA, as a function of ATP demand. In searching for the minimal differences required to explain metabolic function in HCR versus LCR rats, it was determined that the whole-body metabolic phenotype of LCR, compared to the HCR, could be explained by a ~50% reduction in total mitochondrial activity with an additional 5-fold reduction in mitochondrial FA transport activity. Finally, we postulate that over sustained periods of exercise that LCR can partly overcome the initial deficit in FA catabolic activity by upregulating FA transport and/or oxidation processes.
Michael A. Moxley, Kalyan C. Vinnakota, Jason N. Bazil, Nathan R. Qi, Daniel A. Beard
PLoS Comput. Biol.2
2009 BISEN: Biochemical Simulation Environment
abstract
SUMMARY: The Biochemical Simulation Environment (BISEN) is a suite of tools for generating equations and associated computer programs for simulating biochemical systems in the MATLAB computing environment. This is the first package that can generate appropriate systems of differential equations for user-specified multi-compartment systems of enzymes and transporters accounting for detailed biochemical thermodynamics, rapid equilibria of multiple biochemical species and dynamic proton and metal ion buffering. AVAILABILITY: The software and a user manual (including several tutorial examples) are available at bbc.mcw.edu/BISEN.
Joep Vanlier, Fan Wu 0002, Kalyan C. Vinnakota, Ranjan K. Dash, Daniel A. Beard
Bioinform.4