Evidence map›Paper›PMID 30689843›Full record

ArticleDatabase : the journal of biological databases and curation2019

ccPDB 2.0: an updated version of datasets created and compiled from Protein Data Bank.

Piyush Agrawal, Sumeet Patiyal, Rajesh Kumar, Vinod Kumar, Harinder Singh, Pawan Kumar Raghav, Gajendra P S Raghava

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Graph representation learning for structural proteomics.Emerging topics in life sciences · 2021
    Review
  4. DeepDISE: DNA Binding Site Prediction Using a Deep Learning Method.International journal of molecular sciences · 2021
    Article
  5. 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

7 authors.

Piyush AgrawalBioinformatics Center, CSIR-Institute of Microbial Technology, India.
Sumeet PatiyalDepartment of Computational Biology, Indraprastha Institute of Information Technology, Okhla Industrial Estate, Phase III, New Delhi, India.
Rajesh KumarBioinformatics Center, CSIR-Institute of Microbial Technology, India.
Vinod KumarBioinformatics Center, CSIR-Institute of Microbial Technology, India.
Harinder SinghJ. Craig Venter Institute 9605 Medical Center Drive, Suite 150 Rockville, MD, USA.
Pawan Kumar RaghavDepartment of Computational Biology, Indraprastha Institute of Information Technology, Okhla Industrial Estate, Phase III, New Delhi, India.
Gajendra P S RaghavaDepartment of Computational Biology, Indraprastha Institute of Information Technology, Okhla Industrial Estate, Phase III, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ccPDB 2.0 (http://webs.iiitd.edu.in/raghava/ccpdb) is an updated version of the manually curated database ccPDB that maintains datasets required for developing methods to predict the structure and function of proteins. The number of datasets compiled from literature increased from 45 to 141 in ccPDB 2.0. Similarly, the number of protein structures used for creating datasets also increased from ~74 000 to ~137 000 (PDB March 2018 release). ccPDB 2.0 provides the same web services and flexible tools which were present in the previous version of the database. In the updated version, links of the number of methods developed in the past few years have also been incorporated. This updated resource is built on responsive templates which is compatible with smartphones (mobile, iPhone, iPad, tablets etc.) and large screen gadgets. In summary, ccPDB 2.0 is a user-friendly web-based platform that provides comprehensive as well as updated information about datasets.

Indexed as

Database Management SystemsDatabases, ProteinProteinsSoftwareProteins

Identifiers

PMID30689843
PMCPMC6343045

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.