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Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive,…

Computer Vision and Pattern Recognition · Computer Science 2020-09-01 Alexander Hudson , Shaogang Gong

The production processes of proteins in prokaryotic cells are investigated. Most of the mathematical models in the literature study the production of {\em one} fixed type of proteins. When several classes of proteins are considered, an…

Quantitative Methods · Quantitative Biology 2014-11-07 Vincent Fromion , Emanuele Leoncini , Philippe Robert

Protein-Protein Interactions (PPIs) are fundamental in various biological processes and play a key role in life activities. The growing demand and cost of experimental PPI assays require computational methods for efficient PPI prediction.…

Machine Learning · Computer Science 2024-02-23 Lirong Wu , Yijun Tian , Yufei Huang , Siyuan Li , Haitao Lin , Nitesh V Chawla , Stan Z. Li

Post-translational modifications (PTMs) have key roles in extending the functional diversity of proteins and as a result, regulating diverse cellular processes in prokaryotic and eukaryotic organisms. Phosphorylation modification is a vital…

Quantitative Methods · Quantitative Biology 2022-08-10 Farzaneh Esmaili , Mahdi Pourmirzaei , Shahin Ramazi , Seyedehsamaneh Shojaeilangari , Elham Yavari

Understanding protein structure-function relationships is a key challenge in computational biology, with applications across the biotechnology and pharmaceutical industries. While it is known that protein structure directly impacts protein…

Biomolecules · Quantitative Biology 2020-11-02 Nicolas Swenson , Aditi S. Krishnapriyan , Aydin Buluc , Dmitriy Morozov , Katherine Yelick

Learning effective protein representations is critical in a variety of tasks in biology such as predicting protein function or structure. Existing approaches usually pretrain protein language models on a large number of unlabeled amino acid…

Machine Learning · Computer Science 2023-01-31 Zuobai Zhang , Minghao Xu , Arian Jamasb , Vijil Chenthamarakshan , Aurelie Lozano , Payel Das , Jian Tang

We consider the problem of inferring the values of an arbitrary set of variables (e.g., risk of diseases) given other observed variables (e.g., symptoms and diagnosed diseases) and high-dimensional signals (e.g., MRI images or EEG). This is…

Machine Learning · Statistics 2019-02-07 Hao Wang , Chengzhi Mao , Hao He , Mingmin Zhao , Tommi S. Jaakkola , Dina Katabi

The biological function of a protein stems from its 3-dimensional structure, which is thermodynamically determined by the energetics of interatomic forces between its amino acid building blocks (the order of amino acids, known as the…

Biomolecules · Quantitative Biology 2019-05-03 Sean Mullane , Ruoyan Chen , Sri Vaishnavi Vemulapalli , Eli J. Draizen , Ke Wang , Cameron Mura , Philip E. Bourne

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims…

Protein structure-based property prediction has emerged as a promising approach for various biological tasks, such as protein function prediction and sub-cellular location estimation. The existing methods highly rely on experimental protein…

Machine Learning · Computer Science 2023-10-20 Yufei Huang , Siyuan Li , Jin Su , Lirong Wu , Odin Zhang , Haitao Lin , Jingqi Qi , Zihan Liu , Zhangyang Gao , Yuyang Liu , Jiangbin Zheng , Stan. ZQ. Li

As a natural extension of link prediction on graphs, hyperlink prediction aims for the inference of missing hyperlinks in hypergraphs, where a hyperlink can connect more than two nodes. Hyperlink prediction has applications in a wide range…

Machine Learning · Computer Science 2023-07-07 Can Chen , Yang-Yu Liu

The accurate screening of candidate drug ligands against target proteins through computational approaches is of prime interest to drug development efforts. Such virtual screening depends in part on methods to predict the binding affinity…

Machine Learning · Computer Science 2024-10-22 Ho-Joon Lee , Prashant S. Emani , Mark B. Gerstein

In this work, we propose a scalable Bayesian procedure for learning the local dependence structure in a high-dimensional model where the variables possess a natural ordering. The ordering of variables can be indexed by time, the vicinities…

Methodology · Statistics 2021-09-27 Kyoungjae Lee , Lizhen Lin

Understanding protein sequences is vital and urgent for biology, healthcare, and medicine. Labeling approaches are expensive yet time-consuming, while the amount of unlabeled data is increasing quite faster than that of the labeled data due…

Computation and Language · Computer Science 2021-11-01 Liang He , Shizhuo Zhang , Lijun Wu , Huanhuan Xia , Fusong Ju , He Zhang , Siyuan Liu , Yingce Xia , Jianwei Zhu , Pan Deng , Bin Shao , Tao Qin , Tie-Yan Liu

Machine learning models can assign fixed predictions that preclude individuals from changing their outcome. Existing approaches to audit fixed predictions do so on a pointwise basis, which requires access to an existing dataset of…

Machine Learning · Computer Science 2025-07-10 Connor Lawless , Tsui-Wei Weng , Berk Ustun , Madeleine Udell

The calculation of thermodynamic properties of biochemical systems typically requires the use of resource-intensive molecular simulation methods. One example thereof is the thermodynamic profiling of hydration sites, i.e. high-probability…

Biomolecules · Quantitative Biology 2020-01-08 Ahmadreza Ghanbarpour , Amr H. Mahmoud , Markus A. Lill

With recent advancements in the development of artificial intelligence applications using theories and algorithms in machine learning, many accurate models can be created to train and predict on given datasets. With the realization of the…

Machine Learning · Computer Science 2024-03-29 Pei Xi , Lin

The growing interest for comparing protein internal dynamics owes much to the realization that protein function can be accompanied or assisted by structural fluctuations and conformational changes. Analogously to the case of functional…

Biomolecules · Quantitative Biology 2012-12-19 C. Micheletti

Proteins, essential to biological systems, perform functions intricately linked to their three-dimensional structures. Understanding the relationship between protein structures and their amino acid sequences remains a core challenge in…

Quantitative Methods · Quantitative Biology 2024-11-04 Liang He , Peiran Jin , Yaosen Min , Shufang Xie , Lijun Wu , Tao Qin , Xiaozhuan Liang , Kaiyuan Gao , Yuliang Jiang , Tie-Yan Liu

Protein folding is the intricate process by which a linear sequence of amino acids self-assembles into a unique three-dimensional structure. Protein folding kinetics is the study of pathways and time-dependent mechanisms a protein undergoes…

Machine Learning · Computer Science 2023-09-19 Vijay Arvind. R , Haribharathi Sivakumar , Brindha. R