PXD019591

PXD019591 is an original dataset announced via ProteomeXchange.

Title	Machine learning from large-scale proteomics accurately ranks anti-cancer drugs based on efficacy
Description	We present an approach, named Drug Ranking Using ML (DRUML), which uses omics data to produce ordered lists of > 400 drugs based on their effectiveness in decreasing cancer cell proliferation. We trained and validated DRUML using in-house proteomics and phosphoproteomics data from a panel of 26 AML, 10 esophageal and 12 hepatocellular carcinoma cell lines in triplicate (three independent cultures per cell line) by LC-MS/MS
HostingRepository	PRIDE
AnnounceDate	2021-02-22
AnnouncementXML	Submission_2021-02-22_06:22:16.329.xml
DigitalObjectIdentifier	http://dx.doi.org/10.6019/PXD019591
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Supported dataset by repository
PrimarySubmitter	Maruan Hijazi
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	Phospho; Oxidation; Carbamidomethyl; Gln->pyro-Glu
Instrument	Q Exactive Plus

Revision	Datetime	Status	ChangeLog Entry
0	2020-06-04 07:17:54	ID requested
⏵ 1	2021-02-22 06:22:16	announced

Dataset with its publication pending

submitter keyword: machine learning, phosphoproteomics, proteomics, drug efficacy prediction, DRUML, drug ranking, cancer

Pedro Cutillas
contact affiliation	Barts Cancer Institute. Queen Mary University of London
contact email	p.cutillas@qmul.ac.uk
lab head
Maruan Hijazi
contact affiliation	BARTS CANCER INSTITUTE. QUEEN MARY UNIVERSITY OF LONDON
contact email	m.hijazivega@qmul.ac.uk
dataset submitter

Dataset FTP location

PRIDE project URI

• PRIDE
  1. PXD019591
     1. Label: PRIDE project
     2. Name: Machine learning from large-scale proteomics accurately ranks anti-cancer drugs based on efficacy