Recent developments of sequence-based prediction of protein–protein interactions
Author:
Publisher
Springer Science and Business Media LLC
Subject
Molecular Biology,Structural Biology,Biophysics
Link
https://link.springer.com/content/pdf/10.1007/s12551-022-01038-1.pdf
Reference118 articles.
1. Abbasi WA, Yaseen A, Hassan FU, Andleeb S, Minhas F (2020) ISLAND: in-silico proteins binding affinity prediction using sequence information. BioData Min 13(1):20. https://doi.org/10.1186/s13040-020-00231-w
2. AcunerOzbabacan SE, Engin HB, Gursoy A, Keskin O (2011) Transient protein-protein interactions. Protein Eng Des Sel 24(9):635–648. https://doi.org/10.1093/protein/gzr025
3. Alachram H, Chereda H, Beissbarth T, Wingender E, Stegmaier P (2021) Text mining-based word representations for biomedical data analysis and protein-protein interaction networks in machine learning tasks. PLoS ONE 16(10):e0258623. https://doi.org/10.1371/journal.pone.0258623
4. Alanis-Lobato G, Andrade-Navarro MA, Schaefer MH (2017) HIPPIE v.20: enhancing meaningfulness and reliability of protein-protein interaction networks. Nucleic Acids Res 45(D1):D408–D414. https://doi.org/10.1093/nar/gkw985
5. Al-Janabi A (2022) Has DeepMind’s AlphaFold solved the protein folding problem? Biotechniques 72(3):73–76. https://doi.org/10.2144/btn-2022-0007
Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. An Extended Feature Representation Technique for Predicting Sequenced-based Host-pathogen Protein-protein Interaction;Current Bioinformatics;2025-01
2. Insights from Molecular Docking and Dynamics Simulations of P2RX7-αSyn Complex;2024-08-21
3. Unraveling the role of physicochemical differences in predicting protein–protein interactions;The Journal of Chemical Physics;2024-07-25
4. Computational Approaches to Predict Protein–Protein Interactions in Crowded Cellular Environments;Chemical Reviews;2024-03-27
5. A Review of Protein-Protein Interaction Databases;Reference Module in Life Sciences;2024
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3