Evidence map›Paper›PMID 30853739›Full record

ArticleInternational journal of modern physics. B2018

Protein structure prediction.

Haiyou Deng, Ya Jia, Yang Zhang

Abstract read
In one paragraph

Article in International journal of modern physics. B, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Review
  10. Article
  11. AlphaFold, Artificial Intelligence (AI), and Allostery.The journal of physical chemistry. B · 2022
    Review
  12. Article
  13. Review
  14. Article
  15. Review
  16. Graph representation learning for structural proteomics.Emerging topics in life sciences · 2021
    Review
  17. Current Approaches in Supersecondary Structures Investigation.International journal of molecular sciences · 2021
    Review
  18. Article
  19. Review
  20. A DivergentViruses · 2020
    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

3 authors.

Haiyou DengCollege of Science, Huazhong Agricultural University, Wuhan 4R0070, P. R. China.
Ya JiaCollege of Physical Science and Technology, Central China Normal University, Wuhan 430079, P. R. China.
Yang ZhangDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 45108, USA.

Funding

Structure-based functional annotation of microbial genomesR01AI134678 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Lydia Petra Freddolino, SCOTT J. HULTGREN · 2018 to 2026
$6.5M
I-TASSER based atomic-level protein structure predictionR01GM083107 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, YANG · 2008 to 2019
$3.5M
Template-based docking refinement approach to protein-protein structure modelingR01GM116960 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, YANG · 2016 to 2019
$1.4M
NIAID NIH HHS R01 AI134678NIGMS NIH HHS R01 GM083107NIGMS NIH HHS R01 GM116960
6 · The paper itself

Abstract

Predicting 3D structure of protein from its amino acid sequence is one of the most important unsolved problems in biophysics and computational biology. This paper attempts to give a comprehensive introduction of the most recent effort and progress on protein structure prediction. Following the general flowchart of structure prediction, related concepts and methods are presented and discussed. Moreover, brief introductions are made to several widely-used prediction methods and the community-wide critical assessment of protein structure prediction (CASP) experiments.

Indexed as

ab initio predictionhomology modelingProtein structure predictionstructure refinement

Identifiers

PMID30853739
PMCPMC6407873

What OpenQuestion holds

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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.