scispace - formally typeset
L

Lisa Green

Researcher at Broad Institute

Publications -  13
Citations -  1404

Lisa Green is an academic researcher from Broad Institute. The author has contributed to research in topics: Viral evolution & Exome. The author has an hindex of 7, co-authored 13 publications receiving 1212 citations. Previous affiliations of Lisa Green include Massachusetts Institute of Technology.

Papers
More filters
Journal ArticleDOI

Whole genome deep sequencing of HIV-1 reveals the impact of early minor variants upon immune recognition during acute infection

TL;DR: It is concluded that the early control of HIV-1 replication by immunodominant CD8+ T cell responses may be substantially influenced by rapid, low frequency viral adaptations not detected by conventional sequencing approaches, which warrants further investigation.
Journal ArticleDOI

Somatic mutation of CDKN1B in small intestine neuroendocrine tumors

TL;DR: Recurrent somatic mutations and deletions in CDKN1B, the cyclin-dependent kinase inhibitor gene, which encodes p27 are identified, nominating p27 as a tumor suppressor and implicating cell cycle dysregulation in the etiology of SI-NETs.
Journal ArticleDOI

Clinical Acquired Resistance to RAF Inhibitor Combinations in BRAF-Mutant Colorectal Cancer through MAPK Pathway Alterations

TL;DR: Initial characterization of clinical acquired resistance mechanisms to combined RAF/EGFR or RAF/MEK combinations identified several MAPK pathway alterations driving resistance by reactivating MAPK signaling, highlighting the critical dependence of BRAF-mutant colorectal cancers onMAPK signaling and offering potential strategies to overcome resistance.
Journal ArticleDOI

Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms.

TL;DR: An in-depth characterization of the mechanism of sequencer-induced sample contamination due to the phenomenon of index swapping that impacts Illumina sequencers employing patterned flow cells with Exclusion Amplification chemistry is presented and methods for eliminating sample data cross contamination are provided.