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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
PloS one. 2024-07-25; 19.7: e0304060.
Pangenome and genomic signatures linked to the dominance of the lineage-4 of Mycobacterium tuberculosis isolated from extrapulmonary tuberculosis patients in western Ethiopia
Tuberculosis (Edinburgh, Scotland). 2024-07-01; 147.102399.
Predictive biomarkers for latent Mycobacterium tuberculosis infection
Heliyon. 2023-07-04; 9.7: e17958.
Persistent immune and clotting dysfunction detected in saliva and blood plasma after COVID-19
Microorganisms. 2023-04-29; 11.5:
MPrESS: An R-Package for Accurately Predicting Power for Comparisons of 16S rRNA Microbiome Taxa Distributions including Simulation by Dirichlet Mixture Modeling
Critical care (London, England). 2023-04-20; 27.1: 155.
Major adverse cardiovascular events are associated with necroptosis during severe COVID-19
Scientific reports. 2022-12-20; 12.1: 22013.
Author Correction: Sampling from four geographically divergent young female populations demonstrates forensic geolocation potential in microbiomes
Frontiers in microbiology. 2022-12-12; 13.946779.
Gut and lung microbiome profiles in pregnant mice
Scientific reports. 2022-11-03; 12.1: 18547.
Sampling from four geographically divergent young female populations demonstrates forensic geolocation potential in microbiomes
PloS one. 2022-04-05; 17.4: e0265891.
An optimized approach for processing of frozen lung and lavage samples for microbiome studies
Amyotrophic lateral sclerosis & frontotemporal degeneration. 2022-02-01; 23.1-2: 91-99.
Gut microbiome differences between amyotrophic lateral sclerosis patients and spouse controls
Journal of virology. 2021-09-27; 95.20: e0101021.
Kinetic Multi-omic Analysis of Responses to SARS-CoV-2 Infection in a Model of Severe COVID-19
Frontiers in medicine. 2021-06-23; 8.667462.
Urethral Catheter Biofilms Reveal Plasticity in Bacterial Composition and Metabolism and Withstand Host Immune Defenses in Hypoxic Environment
Frontiers in cellular and infection microbiology. 2021-06-04; 11.595554.
Protein and Microbial Biomarkers in Sputum Discern Acute and Latent Tuberculosis in Investigation of Pastoral Ethiopian Cohort
GeroScience. 2021-04-01; 43.2: 593-606.
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
Frontiers in microbiology. 2021-03-23; 12.644861.
Forensic Microbiome Database: A Tool for Forensic Geolocation Meta-Analysis Using Publicly Available 16S rRNA Microbiome Sequencing
Microorganisms. 2020-09-03; 8.9:
Gut Microbial Changes in Diabetic db/db Mice and Recovery of Microbial Diversity upon Pirfenidone Treatment
ACS infectious diseases. 2020-08-14; 6.8: 2120-2129.
Predictive Signatures of 19 Antibiotic-Induced Escherichia coli Proteomes
Gut microbes. 2020-05-03; 11.3: 265-275.
Intestinal and hepatic microbiota changes associated with chronic ethanol administration in mice
Journal of immunology (Baltimore, Md. : 1950). 2020-02-15; 204.4: 796-809.
Type II but Not Type I IFN Signaling Is Indispensable for TLR7-Promoted Development of Autoreactive B Cells and Systemic Autoimmunity
GeroScience. 2019-12-01; 41.6: 907-921.
Gastro-intestinal and oral microbiome signatures associated with healthy aging
Journal of proteome research. 2019-04-05; 18.4: 1907-1915.
Self-Assembled STrap for Global Proteomics and Salivary Biomarker Discovery
Scientific reports. 2018-03-12; 8.1: 4333.
Microbial metagenome of urinary tract infection
Forensic science international. Genetics. 2017-09-01; 30.141-147.
Integrating the microbiome as a resource in the forensics toolkit
Theranostics. 2017-07-07; 7.10: 2704-2717.
Type 1 Diabetes: Urinary Proteomics and Protein Network Analysis Support Perturbation of Lysosomal Function
Biology direct. 2015-03-25; 10.10.
QSAR based model for discriminating EGFR inhibitors and non-inhibitors using Random forest
PloS one. 2014-01-01; 9.10: e105667.
Evaluation of protein dihedral angle prediction methods
PloS one. 2013-01-01; 8.12: e62216.
Improved method for linear B-cell epitope prediction using antigen's primary sequence
Nucleic acids research. 2012-01-01; 40.Database issue: D486-9.
ccPDB: compilation and creation of data sets from Protein Data Bank
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.
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).