Large language models (LLMs) in protein bioinformatics / edited by Dukka B. KC.

Format:

Book

Contributor:

KC, Dukka B., editor.

Series:

Methods in molecular biology (Clifton, N.J.) ; 2941.

Springer protocols (Series)

Methods in Molecular Biology, 1940-6029 ; 2941

Springer protocols

Language:

English

Subjects (All):

Proteins.

Bioinformatics--Data processing.

Bioinformatics.

Artificial intelligence--Biological applications.

Artificial intelligence.

artificial intelligence.

protein.

Physical Description:

1 online resource (xviii, 358 pages) : illustrations (some color).

Place of Publication:

New York, NY : Humana Press, [2025]

Summary:

"This book presents a comprehensive collection of methods, resources, and studies that use large language models (LLMs) in the field of protein bioinformatics. Reflecting the swift pace of LLM development today, the volume delves into numerous LLM-based tools to investigate proteins science, from protein language models to the prediction of protein-ligand binding sites. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice to ensure success in future research. Authoritative and practical, Large Language Models (LLMs) in Protein Bioinformatics serves as an ideal guide for scientists seeking to tap into the potential of artificial intelligence in this vital area of biological study"-- Provided by publisher.

Contents:

A survey of pretrained protein language models / Suresh Pokharel, Pawel Pratyush, Meenal Chaudhari, Michael Heinzinger, Doina Caragea, Hiroto Saigo, and Dukka B. KC

Enhancing structure-aware protein language models with efficient fine-tuning for various protein prediction tasks / Yichuan Zhang, Yongfang Qin, Mahdi Pourmirzaei, Qing Shao, Duolin Wang, and Dong Xu

Exploring ProtFlash : An efficient approach to protein data analysis / Lei Wang, Zhidong Xue, and Yan Wang

Ranking protein–protein models with large language models and graph neural networks / Xiaotong Xu and Alexandre M. J. J. Bonvin

Translating a GO term list to human readable function description using GO2Sum / Swagarika J. Giri, Udayan Pandey, Joon Hong Park, and Daisuke Kihara

TransFun : A tool of integrating large language models, transformers, and equivariant graph neural networks to predict protein function / Frimpong Boadu, Ahhyun Lee, and Jianlin Cheng

Using InterLabelGO+ for accurate protein language model-based function prediction / Chengxin Zhang, Quancheng Liu, and Lydia Freddolino

Functional annotation of proteomes using protein language models : A high-throughput implementation of the ProtTrans model / Ildefonso Cases, Gemma Martínez-Redondo, Rosa Fernández, and Ana M. Rojas

Advances in language-model-informed protein–nucleic acid binding site prediction / Sumit Tarafder, Xinyu Wang, Rahmatullah Roche, and Debswapna Bhattacharya

Practical applications of language models in protein sorting prediction : SignalP 6.0, DeepLoc 2.1, and DeepLocPro 1.0 / Henrik Nielsen

CNN-Meth : A tool to accurately predict lysine methylation sites using evolutionary information-based protein modeling / Austin Spadaro, Alok Sharma, and Iman Dehzangi

Predicting the pathogenicity of human protein variants : Not only a matter of residue labeling / Matteo Manfredi, Gabriele Vazzana, Giulia Babbi, Elisa Bertolini, Castrense Savojardo, Pier Luigi Martelli, and Rita Casadio

A survey of biological function prediction methods with focus on natural language processing (NLP) and large language models (LLM) / Dana Mary Varghese, T. Athulya, Vikash K. Mohani, and Shandar Ahmad

PLMSearch and PLMAlign : Protein language model (PLM)-based homologous protein sequence search and alignment / Wei Liu, Ziye Wang, Ronghui You, Chenghan Xie, Hong Wei, Yi Xiong, Jianyi Yang, and Shanfeng Zhu

Large context, deeper insights : Harnessing large language models for advancing protein–protein interaction analysis / Kaicheng U, Sophia Meixuan Zhang, Suresh Pokharel, Pawel Pratyush, Farah Qaderi, Dongfang Liu, Junhan Zhao, Dukka B. KC, and Siwei Chen

Prediction of protein–peptide binding sites using PepBCL / Ruheng Wang, Kenta Nakai, and Leyi Wei

Predicting peptide bioactivity using the unified model architecture UniDL4BioPep / Zhenjiao Du, Nandan Kumar, and Yonghui Li

CLAPE : Protein–ligand binding site prediction via protein language models / Yufan Liu and Boxue Tian

Large language model (LLM)-based advances in prediction of post-translational modification sites in proteins / Pawel Pratyush, Suresh Pokharel, Stefan Schulze, Lisa Bramer, Robert H. Newman, and Dukka B. KC.

Notes:

Includes bibliographical references and index.

Online resource; title from PDF title page (SpringerLink, viewed July 11, 2025).

Other Format:

Print version: Large language models (LLMs) in protein bioinformatics

ISBN:

9781071646236

1071646230

OCLC:

1527666631

Publisher Number:

CIPO000233396

CIPO000233395

Access Restriction:

Restricted for use by site license