Evidence map›Paper›PMID 35881481›Full record

ArticleDatabase : the journal of biological databases and curation2022

Structural signatures: a web server for exploring a database of and generating protein structural features from human cell lines and tissues.

Nicole Zatorski, David Stein, Rayees Rahman, Ravi Iyengar, Avner Schlessinger

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Database : the journal of biological databases and curation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Nicole ZatorskiDepartment of Pharmacological Sciences, Institute for Systems Biomedicine Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1677 New York, NY 10029, USA.ORCID 0000-0001-5697-4056
David SteinDepartment of Pharmacological Sciences, Institute for Systems Biomedicine Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1677 New York, NY 10029, USA.
Rayees RahmanDepartment of Pharmacological Sciences, Institute for Systems Biomedicine Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1677 New York, NY 10029, USA.
Ravi IyengarDepartment of Pharmacological Sciences, Institute for Systems Biomedicine Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1677 New York, NY 10029, USA.
Avner SchlessingerDepartment of Pharmacological Sciences, Institute for Systems Biomedicine Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1677 New York, NY 10029, USA.ORCID 0000-0003-4007-7814

Funding

Drug Combination Signatures for Prediction and Mitigation of ToxicityU54HG008098 · NHGRI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI BIRTWISTLE, MARC R., SOBIE, ERIC A · 2014 to 2019
$11.8M
Teaching biomedical and pharmacological trainees to produce FAIR data for AI & ML applicationsT32GM062754 · NIGMS · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI SCHLESSINGER, AVNER · 2001 to 2023
$6.2M
Systems Pharmacology for overcoming cell variabilityR01GM137056 · NIGMS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI IYENGAR, SRINIVAS RAVI V · 2020 to 2023
$1.9M
Interdisciplinary Training in Systems and Developmental Biology and Birth DefectsT32HD075735 · NICHD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI JABS, ETHYLIN WANG · 2013 to 2022
$1.8M
Compound Cardiovascular Activity Prediction Using Structural and Genomic FeaturesF30HL160179 · NHLBI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI ZATORSKI, NICOLE · 2021 to 2024
$182k
NHLBI NIH HHS F30 HL160179NICHD NIH HHS T32 HD075735NIGMS NIH HHS R01 GM137056NIH HHS T32 GM062754NIH HHS T32 HD075735NIH HHS U54 HG008098
6 · The paper itself

Abstract

Structural features of proteins provide powerful insights into biological function and similarity. Specifically, previous work has demonstrated that structural features of tissue and drug-treated cell line samples can be used to predict tissue type and characterize drug relationships, respectively. We have developed structural signatures, a web server for annotating and analyzing protein features from gene sets that are often found in transcriptomic and proteomic data. This platform provides access to a structural feature database derived from normal and disease human tissue samples. We show how analysis using this database can shed light on the relationship between states of single-cell RNA-sequencing lung cancer samples. These various structural feature signatures can be visualized on the server itself or downloaded for additional analysis. The structural signatures server tool is freely available at https://structural-server.kinametrix.com/.

Indexed as

ProteomicsSoftwareCell LineDatabases, FactualHumansInternetProteinsProteins

Identifiers

PMID35881481
PMCPMC9319604

What OpenQuestion holds

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LicenceCC BY-NC
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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.