James M McFarland

James M McFarland

Harvard University

H-index: 28

North America-United States

About James M McFarland

James M McFarland, With an exceptional h-index of 28 and a recent h-index of 26 (since 2020), a distinguished researcher at Harvard University, specializes in the field of computational biology, machine learning, cancer biology, computational neuroscience, systems neuroscience.

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

Defining the landscape of cancer vulnerabilities that are engendered by germline genetic variation

Genome-scale functional genomics identify genes preferentially essential for multiple myeloma cells compared to other neoplasias

Dissecting mechanisms underlying FOXR2-mediated gliomagenesis in diffuse midline gliomas

Rapid label-free imaging-based evaluation of cancer dependencies in zero-passage primary cells

TTX-810 is a highly selective novel MCL1 inhibitor with optimized in vivo clearance showing robust efficacy in preclinical solid and hematological tumor models with no effects …

ANJ810 is a novel highly selective MCL1 inhibitor with optimized in vivo clearance and robust efficacy in solid and hematological tumor models

A ubiquitination cascade regulating the integrated stress response and survival in carcinomas

Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal

James M McFarland Information

University

Position

Broad Institute

Citations(all)

8205

Citations(since 2020)

7626

Cited By

2791

hIndex(all)

28

hIndex(since 2020)

26

i10Index(all)

41

i10Index(since 2020)

40

Email

University Profile Page

Google Scholar

James M McFarland Skills & Research Interests

computational biology

machine learning

cancer biology

computational neuroscience

systems neuroscience

Top articles of James M McFarland

Genome-scale functional genomics identify genes preferentially essential for multiple myeloma cells compared to other neoplasias

Nature Cancer

2023/5

Dissecting mechanisms underlying FOXR2-mediated gliomagenesis in diffuse midline gliomas

Cancer Research

2023/4/4

Rapid label-free imaging-based evaluation of cancer dependencies in zero-passage primary cells

Cancer Research

2023/4/4

TTX-810 is a highly selective novel MCL1 inhibitor with optimized in vivo clearance showing robust efficacy in preclinical solid and hematological tumor models with no effects …

2023/4/4

ANJ810 is a novel highly selective MCL1 inhibitor with optimized in vivo clearance and robust efficacy in solid and hematological tumor models

2023/3/3

A ubiquitination cascade regulating the integrated stress response and survival in carcinomas

Cancer discovery

2023/3/1

Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal

Genome Biology

2023/8/23

Phosphate dysregulation via the XPR1–KIDINS220 protein complex is a therapeutic vulnerability in ovarian cancer

Nature cancer

2022/6

Sparse dictionary learning recovers pleiotropy from human cell fitness screens

Cell systems

2022/4/20

Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

bioRxiv

2022/11/19

Rapid prediction of drug responsiveness

2022/10/27

FOXR2 is an epigenetically regulated pan-cancer oncogene that activates ETS transcriptional circuits

Cancer research

2022/9/2

Computational estimation of quality and clinical relevance of cancer cell lines

2022/7

Rapidly evaluating cancer dependencies by label-free imaging of zero-passage primary cells

Cancer Research

2022/6/15

Systematic methods to identify cancer vulnerabilities from genome-wide loss-of-function screens: An interactive framework for target discovery

Cancer Research

2022/6/15

Ancestry bias in CRISPR guide design impedes discovery of genetic dependencies

Cancer Research

2022/6/15

See List of Professors in James M McFarland University(Harvard University)