Kushal K Dey

Kushal K Dey

Harvard University

H-index: 21

North America-United States

About Kushal K Dey

Kushal K Dey, With an exceptional h-index of 21 and a recent h-index of 21 (since 2020), a distinguished researcher at Harvard University, specializes in the field of Computational Biology, Genetics, Genomics, Machine Learning, Biostatistics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Tissue-specific enhancer–gene maps from multimodal single-cell data identify causal disease alleles

Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis

Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types

CRISPR Screening Uncovers a Long-Range Enhancer for ONECUT1 in Pancreatic Differentiation and Links a Diabetes Risk Variant

Systematically characterizing the roles of E3-ligase family members in inflammatory responses with massively parallel Perturb-seq

An encyclopedia of enhancer-gene regulatory interactions in the human genome

Compressed Perturb-seq: highly efficient screens for regulatory circuits using random composite perturbations

Scalable genetic screening for regulatory circuits using compressed Perturb-seq

Kushal K Dey Information

University

Position

Postdoctoral Researcher

Citations(all)

2624

Citations(since 2020)

2366

Cited By

599

hIndex(all)

21

hIndex(since 2020)

21

i10Index(all)

30

i10Index(since 2020)

28

Email

University Profile Page

Harvard University

Google Scholar

View Google Scholar Profile

Kushal K Dey Skills & Research Interests

Computational Biology

Genetics

Genomics

Machine Learning

Biostatistics

Top articles of Kushal K Dey

Title

Journal

Author(s)

Publication Date

Tissue-specific enhancer–gene maps from multimodal single-cell data identify causal disease alleles

Nature Genetics

Saori Sakaue

Kathryn Weinand

Shakson Isaac

Kushal K Dey

Karthik Jagadeesh

...

2024/4/9

Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis

Nature Genetics

Sneha Mitra

Rohan Malik

Wilfred Wong

Afsana Rahman

Alexander J Hartemink

...

2024/3/21

Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types

Nature Communications

Samuel S Kim

Buu Truong

Karthik Jagadeesh

Kushal K Dey

Amber Z Shen

...

2024/1/17

CRISPR Screening Uncovers a Long-Range Enhancer for ONECUT1 in Pancreatic Differentiation and Links a Diabetes Risk Variant

bioRxiv

Samuel Joseph Kaplan

Wilfred Wong

Jielin Yan

Julian Pulecio

Hyein Cho

...

2024

Systematically characterizing the roles of E3-ligase family members in inflammatory responses with massively parallel Perturb-seq

bioRxiv

Kathryn Geiger-Schuller

Basak Eraslan

Olena Kuksenko

Kushal K Dey

Karthik A Jagadeesh

...

2023/1/24

An encyclopedia of enhancer-gene regulatory interactions in the human genome

bioRxiv

Andreas R Gschwind

Kristy S Mualim

Alireza Karbalayghareh

Maya U Sheth

Kushal K Dey

...

2023/11/13

Compressed Perturb-seq: highly efficient screens for regulatory circuits using random composite perturbations

BioRxiv

Douglas Yao

Loic Binan

Jon Bezney

Brooke Simonton

Jahanara Freedman

...

2023/1/23

Scalable genetic screening for regulatory circuits using compressed Perturb-seq

Nature Biotechnology

Douglas Yao

Loic Binan

Jon Bezney

Brooke Simonton

Jahanara Freedman

...

2023/10/23

The Impact of Genomic Variation on Function (IGVF) Consortium

arXiv preprint arXiv:2307.13708

IGVF Consortium

2023/7/24

Rare-variant genetic architecture

Nature Genetics

Wei Li

2023/3

Polygenic architecture of rare coding variation across 394,783 exomes

Nature

Daniel J Weiner

Ajay Nadig

Karthik A Jagadeesh

Kushal K Dey

Benjamin M Neale

...

2023/2/16

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution

Nature genetics

Joyce B Kang

Amber Z Shen

Saisriram Gurajala

Aparna Nathan

Laurie Rumker

...

2023/12

Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data

Nature genetics

Martin Jinye Zhang

Kangcheng Hou

Kushal K Dey

Saori Sakaue

Karthik A Jagadeesh

...

2022/10

SNP-to-gene linking strategies reveal contributions of enhancer-related and candidate master-regulator genes to autoimmune disease

Cell genomics

Kushal K Dey

Steven Gazal

Bryce van de Geijn

Samuel Sungil Kim

Joseph Nasser

...

2022/7/13

Linking disease-associated genetic variants to cell types and processes

Kirsty Minton

2022/12

One step closer to linking GWAS SNPs with the right genes

Nature Genetics

Guillaume Lettre

2022/6

SAIGE-GENE+ improves the efficiency and accuracy of set-based rare variant association tests (vol 54, pg 1446, 2022)

Nature genetics

Wei Zhou

Wenjian Bi

Zhangchen Zhao

Kushal K Dey

Karthik A Jagadeesh

...

2022/10

Single-cell RNA-seq relates GWAS variants to disease risk

Nature Biotechnology

Anne Dörr

2022/11

Combining SNP-to-gene linking strategies to identify disease genes and assess disease omnigenicity

Nature genetics

Steven Gazal

Omer Weissbrod

Farhad Hormozdiari

Kushal K Dey

Joseph Nasser

...

2022/6

Identifying disease-critical cell types and cellular processes by integrating single-cell RNA-sequencing and human genetics

Nature genetics

Karthik A Jagadeesh

Kushal K Dey

Daniel T Montoro

Rahul Mohan

Steven Gazal

...

2022/10

See List of Professors in Kushal K Dey University(Harvard University)

Co-Authors

H-index: 88
Matthew Stephens

Matthew Stephens

University of Chicago

H-index: 35
Jesse Engreitz, PhD

Jesse Engreitz, PhD

Stanford University

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