Protein function prediction : methods and protocols / edited by Lukasz Kurgan, Daisuke Kihara

Format:

Book

Contributor:

Kurgan, Lukasz, editor.

Kihara, Daisuke, editor.

Series:

Methods in molecular biology (Clifton, N.J.) ; v. 2947.

Springer protocols (Series)

Methods in molecular biology, 1940-6029 ; 2947

Springer protocols

Language:

English

Subjects (All):

Proteins--Laboratory manuals.

Proteins.

Protein-protein interactions--Laboratory manuals.

Protein-protein interactions.

Physical Description:

1 online resource : illustrations

black and white

illustrations

Edition:

Second edition

Place of Publication:

New York, NY : Humana Press, [2025]

Summary:

"This fully updated volume explores a wide array of new and state-of-the-art tools and resources for protein function prediction. Beginning with in-depth overviews of essential underlying computational techniques, such as machine learning, multi-task learning, protein language models, and deep learning, the book continues by covering specific tools for protein function prediction, ranging from gene ontology-term predictions to the predictions of binding sites, protein localization and solubility, signal peptides, intrinsic disorder, and intrinsically disordered binding regions, as well as presenting databases that address protein moonlighting and protein binding. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, step-by-step instructions on how to use software and web resources, use cases, and tips on troubleshooting and avoiding known pitfalls. Authoritative and up-to-date, Protein Function Prediction: Methods and Protocols, Second Edition helps readers to understand and appreciate this vibrant and growing research area and guides in the quest to identify and use the best computational methods and resources for their projects"-- Springer Nature Link

Contents:

Computational prediction of protein functional annotations / Maxat Kulmanov and Robert Hoehndorf

Machine learning for protein function prediction / Yi-Heng Zhu, Zi Liu, Yu Ding, Zhiwei Ji, and Dong-Jun Yu

Graph neural network-based approaches for protein function prediction / Meenal Chaudhari, Soufia Bahmani, Pawel Pratyush, Steven Garrett, Neel J. Thapa, and Dukka B. KC

Multitask learning-based approaches for protein function prediction / Soufia Bahmani, Meenal Chaudhari, Calen Carrier, Steven Garrett, Pawel Pratyush, and Dukka B. KC

A survey of deep learning methods and tools for protein binding site prediction / Alina Rohulia, Yanli Wang, and Jianlin Cheng

A survey of current status in AI-based topology prediction of transmembrane proteins / Divyangana Bathla, Richa Mishra, and Shandar Ahmad

NetGO 3.0 : a recent protein function prediction tool based on protein language model / Shaojun Wang, Hancheng Liu, Ronghui You, Yunjia Liu, Yi Xiong, and Shanfeng Zhu

Predicting protein functions with function-aware domain embeddings using Domain-PFP / Nabil Ibtehaz and Daisuke Kihara

Integrating gene ontology relationships for protein function prediction using PFresGO / Tong Pan, Geoffrey I. Webb, Seiya Imoto, and Jiangning Song

Annotating genomes with DeepGO protein function prediction tools / Rund Tawfiq, Kexin Niu, Maxat Kulmanov, and Robert Hoehndorf

An online server for geometry-aware protein function annotations through predicted structure / Jialin Zou, Qianmu Yuan, and Yuedong Yang

Exploring binding sites on proteins for function prediction using the PoSSuM databases / Kentaro Tomii and Kazuyoshi Ikeda

Comprehensive prediction of protein localization and signal peptides using MULocDeep / Lei Jiang, Weinan Zhang, Shuai Zeng, Yuexu Jiang, and Dong Xu

A benchmarking platform for assessing protein language models on function-related prediction tasks / Elif Çevrim, Melih Gökay Yiğit, Erva Ulusoy, Ardan Yılmaz, and Tunca Doğan

Prediction of intrinsic disorder functions with DEPICTER2 / Sushmita Basu and Lukasz Kurgan

Prediction of disordered linear interacting peptides with CLIP / Jiahui Liang, Zhenling Peng, and Lukasz Kurgan

Prediction of intrinsically disordered lipid binding residues with DisoLipPred / Bi Zhao and Lukasz Kurgan

NaviGO : an interactive tool for gene ontology functional analysis with free text GO summaries / Swagarika J. Giri, Udayan Pandey, Joon Hong Park, and Daisuke Kihara

Using the MoonProt database for understanding protein functions / Constance J. Jeffery

Illustrative features and utilities of MPAD : thermodynamic database for membrane protein–protein complexes / Fathima Ridha and M. Michael Gromiha

Notes:

Includes bibliographical references and index

Online resource; title from PDF title page (Springer Nature Link, viewed July 28, 2026)

Other Format:

Print version: Protein function prediction

ISBN:

9781071646625

1071646621

OCLC:

1531575893

Publisher Number:

CIPO000272476

Access Restriction:

Restricted for use by site license