dinesh barupal

Assistant Professor

Icahn School of Medicine at Mount Sinai

United States

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Dr. Dinesh Barupal is an Assistant Professor at the Icahn School of Medicine at Mt Sinai, located in the United States. His research interests encompass human exposomics, metabolomics, and the effects of microbiome-derived metabolites on health, with recent publications addressing liver cancer risk, gestational diabetes, and cognitive decline. He is also involved in developing advanced analytical frameworks and methodologies for chemical annotation and data interpretation in metabolomics.

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2020

Collaborators (14)

Elliott J. Price

Masaryk University

CZECH REPUBLIC

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Matthias Arnold

Adj. Associate Professor

Duke University

UNITED STATES

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David Klurfeld

Adjunct Professor

Indiana State University

UNITED STATES

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Anarina Murillo

New York University

UNITED STATES

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Alejo Nevado-Holgado

University of Oxford

UNITED KINGDOM

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Oliver Fiehn

Professor

University of California, Davis

UNITED STATES

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Priyanka Baloni

Assistant Professor

Purdue University

UNITED STATES

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Taeho Jo

Assistant Professor

Indiana University School of Medicine

UNITED STATES

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Stefano Papazian

Head of Exposomics Facility, SciLifeLab

Stockholm University

SWEDEN

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Peter Meikle

Head

Baker Heart and Diabetes Institute

AUSTRALIA

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Katherine Maloney

Professor

Point Loma Nazarene University

UNITED STATES

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Arnaud Germain

Cornell University

UNITED STATES

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Jennifer S. Labus

University of California, Los Angeles

UNITED STATES

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Louis-Felix NOTHIAS

Chaire de Professeur Junior CNRS

Institut national de la recherche scientifique

FRANCE

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dinesh barupal

Research Interests

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About

Articles (20)

High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage

Peripheral inflammation is associated with brain atrophy and cognitive decline linked to mild cognitive impairment and Alzheimer’s disease

Advisory Group recommendations on priorities for the IARC Monographs

IDSL.GOA: gene ontology analysis for interpreting metabolomic datasets

IDSL_MINT: a deep learning framework to predict molecular fingerprints from mass spectra

Microbiome-derived metabolites in early to mid-pregnancy and risk of gestational diabetes: a metabolome-wide association study

Identification of pre‐diagnostic lipid sets associated with liver cancer risk using untargeted lipidomics and chemical set analysis: A nested case‐control study within the ATBC cohort

Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets

In utero metabolomic signatures of refined grain intake and risk of gestational diabetes: A metabolome-wide association study

Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data

Prioritizing cancer hazard assessments for IARC Monographs using an integrated approach of database fusion and text mining

Metabolic Network Analysis Reveals Altered Bile Acid Synthesis and Metabolism in Alzheimer’s Disease

A lipidome-wide association study of the lipoprotein insulin resistance index

Functional Microbiomics Reveals Alterations of the Gut Microbiome and Host Co-Metabolism in Patients With Alcoholic Hepatitis.

Comprehensive Circulatory Metabolomics in ME/CFS Reveals Disrupted Metabolism of Acyl Lipids and Steroids

A Pilot Study on the Effect of Prebiotic on Host-Microbial Co-metabolism in Peritoneal Dialysis Patients

Perspective: Dietary Biomarkers of Intake and Exposure - Exploration with Omics Approaches

Retip: Retention Time Prediction for Compound Annotation in Untargeted Metabolomics

Serum triglycerides in Alzheimer disease: Relation to neuroimaging and CSF biomarkers

Collaborators (14)

Elliott J. Price

Matthias Arnold

David Klurfeld

Anarina Murillo

Alejo Nevado-Holgado

Oliver Fiehn

Priyanka Baloni

Taeho Jo

Stefano Papazian

Peter Meikle

Katherine Maloney

Arnaud Germain

Jennifer S. Labus

Louis-Felix NOTHIAS

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