Evidence map›Paper›PMID 34758444›Full record

ArticleJournal of the mechanical behavior of biomedical materials2022

ColGen: An end-to-end deep learning model to predict thermal stability of de novo collagen sequences.

Chi-Hua Yu, Eesha Khare, Om Prakash Narayan, Rachael Parker, David L Kaplan, Markus J Buehler

Open access · greenAbstract read
In one paragraph

Article in Journal of the mechanical behavior of biomedical materials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

9 citing papers in PubMed, 34 citations in OpenAlex.

  1. Review
  2. Review
  3. De Novo Design of Specific Heterotrimeric Collagen-Like Peptides via Genetic Algorithm.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Learning deep representations of enzyme thermal adaptation.Protein science : a publication of the Protein Society · 2022
    Article
  9. 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

6 authors at 2 institutions in 2 countries.

Chi-Hua YuDepartment of Engineering Science, National Cheng Kung University, No. 1 University Road, Tainan, 701, Taiwan; Laboratory for Atomistic and Molecular Mechanics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA.
Eesha KhareLaboratory for Atomistic and Molecular Mechanics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA; Department of Materials Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA.
Om Prakash NarayanDepartment of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA.
Rachael ParkerDepartment of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA.
David L KaplanDepartment of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA.
Markus J BuehlerLaboratory for Atomistic and Molecular Mechanics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA; Center for Computational Science and Engineering, Schwarzman College of Computing, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA, 02139, USA; Center for Materials Science and Engineering, 77 Massachusetts Ave, Cambridge, MA, 02139, USA. Electronic address: mbuehler@mit.edu.
Massachusetts Institute of Technology · USTufts University · US

Funding

Tissue Engineering Resource Center: TTDP41EB027062 · NIBIB · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Gordana Vunjak-Novakovic · 2019 to 2026
$12.6M
Models to Predict Protein Biomaterial PerformanceU01EB014976 · NIBIB · TUFTS UNIVERSITY MEDFORD · PI BUEHLER, MARKUS J., KAPLAN, DAVID L. · 2012 to 2020
$5.2M
NIBIB NIH HHS P41 EB027062NIBIB NIH HHS U01 EB014976
6 · The paper itself

Abstract

Collagen is the most abundant structural protein in humans, with dozens of sequence variants accounting for over 30% of the protein in an animal body. The fibrillar and hierarchical arrangements of collagen are critical in providing mechanical properties with high strength and toughness. Due to this ubiquitous role in human tissues, collagen-based biomaterials are commonly used for tissue repairs and regeneration, requiring chemical and thermal stability over a range of temperatures during materials preparation ex vivo and subsequent utility in vivo. Collagen unfolds from a triple helix to a random coil structure during a temperature interval in which the midpoint or T

Indexed as

Deep LearningAnimalsBiocompatible MaterialsCollagenHumansTemperatureWound HealingBiocompatible MaterialsCollagenCollagenDeep learningLong short-term memory artificial recurrent neural networkMachine learningMelting temperature

Identifiers

PMID34758444
PMCPMC9514290
OpenAlexW3209986690

What OpenQuestion holds

Textmetadata
LicenceTDM
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.