Harinder Singh, PhD

Staff Scientist

Harinder Singh, PhD is a Staff Scientist in the Infectious Disease Department at the J. Craig Venter Institute (JCVI). Dr. Singh's area of research is mostly focused on various data analysis, data mining, development of prediction algorithm and databases and bioinformatics pipelines for the scientific community. Dr. Singh has significant experience in analyzing proteomics, metabolomics, expression, microbiome and metagenomics datasets using various bioinformatics pipelines. Dr. Singh's interest lies in understanding the long-term effects of diabetes and predict bio-signature with the progression of diabetes using meta-omics dataset and system biology. Dr. Singh received his PhD from CSIR-Institute of Microbial Technology in Bioinformatics and obtained his master’s degree in biotechnology from Thapar University, INDIA.

Research Priorities

Analysis of microbiomes using metagenomics
  • Understanding human disease diagnosis and progression due to changes in the microbiome.
  • Prediction of geo-location based on the personal microbiome.
Understanding diabetes and chronic kidney diseases
  • Protein biomarkers for diagnosis and progression of diabetes and chronic kidney disease.
Development of Bioinformatics tools
  • Pipeline for analyzing different ‘omics data.
  • Development of prediction methods for understanding complex datasets.
  • Management and development of databases and web-based applications.

Publications

Protein signatures from blood plasma and urine suggest changes in vascular function and IL-12 signaling in elderly with a history of chronic diseases compared with an age-matched healthy cohort.
GeroScience. 2020-09-24;
PMID: 32974878
Gut Microbial Changes in Diabetic db/db Mice and Recovery of Microbial Diversity upon Pirfenidone Treatment.
Microorganisms. 2020-09-03; 8.9:
PMID: 32899353
Predictive Signatures of 19 Antibiotic-Induced Escherichia coli Proteomes.
ACS infectious diseases. 2020-08-14; 6.8: 2120-2129.
PMID: 32673475
Intestinal and hepatic microbiota changes associated with chronic ethanol administration in mice.
Gut microbes. 2020-05-03; 11.3: 265-275.
PMID: 30982395
Type II but Not Type I IFN Signaling Is Indispensable for TLR7-Promoted Development of Autoreactive B Cells and Systemic Autoimmunity.
Journal of immunology (Baltimore, Md. : 1950). 2020-02-15; 204.4: 796-809.
PMID: 31900342
Gastro-intestinal and oral microbiome signatures associated with healthy aging.
GeroScience. 2019-12-01; 41.6: 907-921.
PMID: 31620923
Self-Assembled STrap for Global Proteomics and Salivary Biomarker Discovery.
Journal of proteome research. 2019-04-05; 18.4: 1907-1915.
PMID: 30848925
Microbial metagenome of urinary tract infection.
Scientific reports. 2018-03-12; 8.1: 4333.
PMID: 29531289
Integrating the microbiome as a resource in the forensics toolkit.
Forensic science international. Genetics. 2017-09-01; 30.141-147.
PMID: 28728057
Type 1 Diabetes: Urinary Proteomics and Protein Network Analysis Support Perturbation of Lysosomal Function.
Theranostics. 2017-07-07; 7.10: 2704-2717.
PMID: 28819457
QSAR based model for discriminating EGFR inhibitors and non-inhibitors using Random forest.
Biology direct. 2015-03-25; 10.10.
PMID: 25880749
Evaluation of protein dihedral angle prediction methods.
PloS one. 2014-01-01; 9.10: e105667.
PMID: 25166857
Improved method for linear B-cell epitope prediction using antigen's primary sequence.
PloS one. 2013-01-01; 8.12: e62216.
PMID: 23667458
ccPDB: compilation and creation of data sets from Protein Data Bank.
Nucleic acids research. 2012-01-01; 40.Database issue: D486-9.
PMID: 22139939

Research Priorities

Analysis of microbiomes using metagenomics
  • Understanding human disease diagnosis and progression due to changes in the microbiome.
  • Prediction of geo-location based on the personal microbiome.
Understanding diabetes and chronic kidney diseases
  • Protein biomarkers for diagnosis and progression of diabetes and chronic kidney disease.
Development of Bioinformatics tools
  • Pipeline for analyzing different ‘omics data.
  • Development of prediction methods for understanding complex datasets.
  • Management and development of databases and web-based applications.

Gut Microbiome Sysbiosis in Childhood Acute Lymphoblastic Leukemia (ALL) Patients

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Biomarker Discovery and Systems Biology for Types 1 and 2 Diabetes and Healthy Aging

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Genomics and Proteomics Approaches to T1D

This study addresses the complex interactions between the host and environmental factors as they relate to the development of Type I Diabetes (T1D). 

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Human Hair Microbiota

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