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Chris Sander

Researcher at Harvard University

Publications -  730
Citations -  273726

Chris Sander is an academic researcher from Harvard University. The author has contributed to research in topics: Large Hadron Collider & Protein structure. The author has an hindex of 178, co-authored 713 publications receiving 233287 citations. Previous affiliations of Chris Sander include Purdue University & University of Leeds.

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Journal ArticleDOI

Search for bottom-squark pair production in pp collision events at s =13 TeV with hadronically decaying τ -leptons, b -jets, and missing transverse momentum using the ATLAS detector

Georges Aad, +2972 more
- 01 Aug 2021 - 
TL;DR: In this paper, a search for pair production of bottom quarks in events with hadronically decaying τ-leptons, b-tagged jets, and large missing transverse momentum is presented.

The molecular landscape of oncogenic signaling pathways in The Cancer Genome Atlas

Francisco Sanchez-Vega, +37 more
Posted ContentDOI

Adaptive response to BET inhibition induces therapeutic vulnerability to MCL1 inhibitors in breast cancer

Gonghong Yan, +16 more
- 21 Mar 2020 - 
TL;DR: It is demonstrated that BET inhibition induces a multi-faceted adaptive response program leading to MCL1 protein-driven evasion of apoptosis in breast cancers, which suggests co-targeting MCL 1 and BET is highly synergistic inin vitro and in vivobreast cancer models.
Posted ContentDOI

Learning from pre-pandemic data to forecast viral escape

Nicole N. Thadani, +7 more
- 12 Apr 2023 - 
TL;DR: A biologically grounded model to quantify the viral escape potential of mutations at scale, EVEscape, which brings together fitness predictions from evolutionary models, structure-based features that assess antibody binding potential, and distances between mutated and wild-type residues.

scPerturb: Information Resource for Harmonized Single-Cell Perturbation Data

Stefan Peidli, +9 more
TL;DR: This work collects a set of 44 publicly available single-cell perturbation-response datasets with molecular readouts, including transcriptomics, proteomics and epigenomics, and demonstrates the application of E-distance for quantifying perturbations similarity and strength.