Dr. Veselkov's research group focuses on developing computational methods that can make a difference in data-driven global health and disease. He has led the development of a series of field-changing data analytics frameworks to augment emerging molecular ("-omics") profiling technologies into clinical decision support, and population health management. His group expertise combines the use of a diverse range of computational techniques from signal processing, imaging informatics, machine learning, natural language processing and highperformance computing for information extraction from heterogeneous biomedical datasets. His translation interests are precision medicine and digital pathology. Dr Veselkov has received a World Economic Forum (WEF) Young Scientist Award, and currently serves as an active member of the WEF Global Agenda Council on the Future of Computing.
BASIS: BIOINFORMATICS PLATFORM FOR PROCESSING LARGE-SCALE MASS SPECTROMETRY IMAGING IN CHEMICALLY AUGMENTED HISTOLOGY
Veselkov KA*, et al (2018) BASIS: High-performance bioinformatics platform for processing of large-scale mass spectrometry imaging data in chemically augmented histology, SCIENTIFIC REPORTS.
Veselkov KA*,et al (2014).Chemo-informatic strategy for imaging mass spectrometry-based hyperspectral profiling of lipid signatures in colorectal cancer, PNAS, 111: 1216-122.
DRUGS: DATA ANALYTICS PLATFORM FOR DRUG REPOSITIONING USING GRIDS OF SMARTPHONES
Galea D, Inglese P, Cammack L,Strittmatter N, Rebec M, Mirnezami R, Laponogov I, Kinross J, Nicholson J, Takats Z, Veselkov KA* (2017), Translational utility of a hierarchical classification strategy in biomolecular data analytics, SCIENTIFIC REPORTS, 7, 14981
CHEMDISTILLER AND MSHUB: PROCESSING, ANNOTATION AND INTERROGATION OF LARGE-SCALE CHROMATOGRAPHY-MASS SPECTROMETRY DATA
Laponogov I, Sadawi N, Dieter G, Mirnezami R, Veselkov K* (2018) ChemDistiller: an engine for metabolite annotation in mass spectrometry, BIOINFORMATICS.
HASKEE: HYPOTHESIS AND ASSOCIATIONS FROM KNOWLEDGE AND EVIDENCE NATURAL LANGUAGE PROCESSING PLATFORM
Galea D, Laponogov I, Veselkov K* (2018), Exploiting and assessing multi-source textual data for supervised biomedical named entity recognition, BIOINFORMATICS
Gu Q, Veselkov K, 2018, Bi-clustering of metabolic data using matrix factorization tools, Methods, Vol:151, ISSN:1046-2023, Pages:12-20
Galea D, Laponogov I, Veselkov K, 2018, Exploiting and assessing multi-source data for supervised biomedical named entity recognition, Bioinformatics, Vol:34, ISSN:1367-4803, Pages:2472-2482
et al., 2018, ChemDistiller: an engine for metabolite annotation in mass spectrometry, Bioinformatics, Vol:34, ISSN:1367-4803, Pages:2096-2102
et al., 2018, BASIS: High-performance bioinformatics platform for processing of large-scale mass spectrometry imaging data in chemically augmented histology, Scientific Reports, Vol:8, ISSN:2045-2322
et al., 2017, Translational utility of a hierarchical classification strategy in biomolecular data analytics., Scientific Reports, Vol:7, ISSN:2045-2322
et al., 2014, Chemo-informatic strategy for imaging mass spectrometry-based hyperspectral profiling of lipid signatures in colorectal cancer, Proceedings of the National Academy of Sciences of the United States of America, Vol:111, ISSN:0027-8424, Pages:1216-1221
et al., 2011, Optimized Preprocessing of Ultra-Performance Liquid Chromatography/Mass Spectrometry Urinary Metabolic Profiles for Improved Information Recovery, Analytical Chemistry, Vol:83, ISSN:0003-2700, Pages:5864-5872
et al., 2010, A Metabolic Entropy Approach for Measurements of Systemic Metabolic Disruptions in Patho-Physiological States, Journal of Proteome Research, Vol:9, ISSN:1535-3893, Pages:3537-3544
et al., 2009, Recursive Segment-Wise Peak Alignment of Biological H-1 NMR Spectra for Improved Metabolic Biomarker Recovery, Analytical Chemistry, Vol:81, ISSN:0003-2700, Pages:56-66
et al., 2008, Human metabolic phenotype diversity and its association with diet and blood pressure, Nature, Vol:453, ISSN:0028-0836, Pages:396-U50