Evidence map›Paper›PMID 30395160›Full record

ArticleBioinformatics (Oxford, England)2019

DrugThatGene: integrative analysis to streamline the identification of druggable genes, pathways and protein complexes from CRISPR screens.

Matthew C Canver, Daniel E Bauer, Takahiro Maeda, Luca Pinello

Open access · bronzeAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 39% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 2 countries.

Matthew C CanverMolecular Pathology Unit, Center for Computational and Integrative Biology, Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA.
Daniel E BauerDivision of Hematology/Oncology, Boston Children's Hospital, Boston, USA.
Takahiro MaedaCenter for Cellular and Molecular Medicine, Kyushu University Hospital, Fukuoka, Japan.
Luca PinelloMolecular Pathology Unit, Center for Computational and Integrative Biology, Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA.
Center for Cancer Research · USDana-Farber Cancer Institute · USHarvard University · USKyushu University Hospital · JP

Funding

TRANSCRIPTION FACTOR GATA-1 IN TERMINAL ERYTHROID DEVELOPMENTP01HL032262 · NHLBI · CHILDREN'S HOSPITAL BOSTON · PI ORKIN, STUART H · 1985 to 2021
$38.9M
Center for Genomic Editing and Recording: Development and Application of Next-Generation Genome and Epigenome Editing Methods to Advance the Study and Treatment of Human DiseaseRM1HG009490 · NHGRI · WHITEHEAD INSTITUTE FOR BIOMEDICAL RES · PI Brittany S. Adamson, Martin Joseph Ankrah Aryee · 2017 to 2026
$22.7M
High-throughput discovery of essential noncoding sequences for erythropoiesisDP2HL137300 · NHLBI · BOSTON CHILDREN'S HOSPITAL · PI BAUER, DANIEL EVAN · 2016 to 2016
$2.7M
Targeting the NuRD complex for fetal globin inductionR01DK111455 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI BERLINER, NANCY, MAEDA, TAKAHIRO · 2016 to 2020
$2.0M
Discovering disease-causal variants by linking genetic and epigenetic variationR00HG008399 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI PINELLO, LUCA · 2017 to 2019
$747k
Epigenetic regulation of BCL11A in the hemoglobin switchK08DK093705 · NIDDK · BOSTON CHILDREN'S HOSPITAL · PI BAUER, DANIEL EVAN · 2012 to 2016
$679k
Identification of sequences and factors required for HbF repressionR03DK109232 · NIDDK · BOSTON CHILDREN'S HOSPITAL · PI BAUER, DANIEL EVAN · 2016 to 2017
$226k
Targeting the transcription machinery for fetal globin inductionR56DK105001 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI MAEDA, TAKAHIRO · 2015 to 2015
$142k
Identification of Novel Regulators of Fetal Hemoglobin ExpressionF30DK103359 · NIDDK · HARVARD MEDICAL SCHOOL · PI CANVER, MATTHEW CHARLES · 2015 to 2017
$131k
NHGRI NIH HHS R00 HG008399NHGRI NIH HHS RM1 HG009490NHLBI NIH HHS DP2 HL137300NHLBI NIH HHS P01 HL032262NIDDK NIH HHS F30 DK103359NIDDK NIH HHS K08 DK093705NIDDK NIH HHS R01 DK111455NIDDK NIH HHS R03 DK109232
6 · The paper itself

Abstract

motivationThe clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) nuclease system has allowed for high-throughput, large scale pooled screens for functional genomic studies. To aid in the translation of functional genomics to therapeutics, we developed DrugThatGene (DTG) as a web-based application that streamlines analysis of potential therapeutic targets identified from functional genetic screens.

resultsStarting from a gene list as input, DTG offers automated identification of small molecules along with supporting information from human genetic and other relevant databases. Furthermore, DTG aids in the identification of common biological pathways and protein complexes in conjunction with associated small molecule inhibitors. Taken together, DTG aims to expedite the identification of small molecules from the abundance of functional genetic data generated from CRISPR screens. AVAILABILITY AND IMPLEMENTATION: DTG is an open-source and free software available as a website at http://drugthatgene.pinellolab.org. Source code is available at: https://github.com/pinellolab/DrugThatGene, which can be downloaded in order to run DTG locally.

Indexed as

Clustered Regularly Interspaced Short Palindromic RepeatsCRISPR-Cas SystemsEndonucleasesHumansSoftwareEndonucleases

Identifiers

PMID30395160
PMCPMC6546128
OpenAlexW2899672494

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.