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Author

Ritesh Krishna

Observed names: Krishna, Ritesh, R Krishna, R. KRISHNA
Observed institutions: National Institutes of Health, IBM (United States), University of Liverpool, Science and Technology Facilities Council, Daresbury Laboratory, University of Warwick, Sci-Tech Daresbury, IBM (United Kingdom), National Cancer Institute
ORCID: 0000-0002-5303-1412
Observed ORCID: 0000-0002-5303-1412
OpenAlex ID: A5078961975
The microRNA expression changes associated with malignancy and SDHB mutation in pheochromocytoma
2012 · E Patterson, R Webb, et al. · Endocrine Related Cancer · 66
How to manipulate landscapes to improve the potential for range expansion
2016 · Jenny A. Hodgson, David W. Wallis, et al. · Methods in Ecology and Evolution · 42
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ProteoAnnotator – Open source proteogenomics annotation software supporting PSI standards
2014 · Fawaz Ghali, Ritesh Krishna, et al. · PROTEOMICS · 40
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Tools (Viewer, Library and Validator) that Facilitate Use of the Peptide and Protein Identification Standard Format, Termed mzIdentML
2013 · Fawaz Ghali, Ritesh Krishna, et al. · Molecular & Cellular Proteomics · 40
Using human in vitro transcriptome analysis to build trustworthy machine learning models for prediction of animal drug toxicity
2020 · Laura-Jayne Gardiner, Anna Paola Carrieri, et al. · Scientific Reports · 31
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jmz I dent ML API : A J ava interface to the mz I dent ML standard for peptide and protein identification data
2012 · Florian Reisinger, Ritesh Krishna, et al. · PROTEOMICS · 29
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Interpreting machine learning models to investigate circadian regulation and facilitate exploration of clock function
2021 · Laura-Jayne Gardiner, Rachel Rusholme-Pilcher, et al. · Proceedings of the National Academy of Sciences · 28
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Stage-specific Proteomes from Onchocerca ochengi, Sister Species of the Human River Blindness Parasite, Uncover Adaptations to a Nodular Lifestyle
2016 · Stuart D. Armstrong, Dong Xia, et al. · Molecular & Cellular Proteomics · 27
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Arable soil nitrogen dynamics reflect organic inputs via the extended composite phenotype
2022 · Andrew L. Neal, Harry A. Barrat, et al. · Nature Food · 22
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Large-scale and significant expression from pseudogenes in Sodalis glossinidius – a facultative bacterial endosymbiont
2020 · Ian Goodhead, Frances Blow, et al. · Microbial Genomics · 22
A large‐scale proteogenomics study of apicomplexan pathogens—Toxoplasma gondii and Neospora caninum
2015 · Ritesh Krishna, Dong Xia, et al. · PROTEOMICS · 21
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Parasites, proteomes and systems: has Descartes’ clock run out of time?
2012 · J. M. WASTLING, S. D. ARMSTRONG, et al. · Parasitology · 18
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FDRAnalysis: A Tool for the Integrated Analysis of Tandem Mass Spectrometry Identification Results from Multiple Search Engines
2011 · David C. Wedge, Ritesh Krishna, et al. · Journal of Proteome Research · 18
The sequence of a male-specific genome region containing the sex determination switch in Aedes aegypti
2018 · Joe Turner, Ritesh Krishna, et al. · Parasites & Vectors · 13
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Re-purposing software for functional characterization of the microbiome
2021 · Laura-Jayne Gardiner, Niina Haiminen, et al. · Microbiome · 12
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Accelerating molecular discovery through data and physical sciences: Applications to peptide-membrane interactions
2018 · Flaviu Cipcigan, Anna Paola Carrieri, et al. · The Journal of Chemical Physics · 12
A temporal precedence based clustering method for gene expression microarray data
2010 · Ritesh Krishna, Chang-Tsun Li, et al. · BMC Bioinformatics · 11
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Listen to Genes: Dealing with Microarray Data in the Frequency Domain
2009 · Jianfeng Feng, Dongyun Yi, et al. · PLoS ONE · 11
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A Partial Granger Causality Approach to Explore Causal Networks Derived From Multi-parameter Data
2008 · Ritesh Krishna, Shuixia Guo · Lecture notes in computer science · 11
The jmz Q uant ML programming interface and validator for the mz Q uant ML data standard
2014 · Da Qi, Ritesh Krishna, et al. · PROTEOMICS · 9
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Hierarchically Labeled Database Indexing Allows Scalable Characterization of Microbiomes
2020 · Filippo Utro, Niina Haiminen, et al. · iScience · 7
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A guide for integration of proteomic data standards into laboratory workflows
2012 · J. Alberto Medina‐Aunon, Ritesh Krishna, et al. · PROTEOMICS · 7
A partial Granger causality based method for analysis of parameter interactions in bioreactors
2010 · Ritesh Krishna, Satyadarshi Nanda, et al. · Computers & Chemical Engineering · 7
Bluster or Lustre: Can AI Improve Crops and Plant Health?
2021 · Laura-Jayne Gardiner, Ritesh Krishna · Plants · 6
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DGCNN approach links metagenome-derived taxon and functional information providing insight into global soil organic carbon
2024 · Laura-Jayne Gardiner, Matthew Marshall, et al. · npj Biofilms and Microbiomes · 5
Works count: 44
Citation count: 526
H-index: 13
I10-index: 19
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