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The past decade has witnessed the development and success of coarse-grained network models of proteins for predicting many equilibrium properties related to collective modes of motion. Curiously, the results are usually robust towards the…

Molecular Networks · Quantitative Biology 2008-09-23 Canan Atilgan , Ibrahim Inanc , Ali Rana Atilgan

The proper biological functioning of proteins often relies on the occurrence of coordinated fluctuations around their native structure, or of wider and sometimes highly elaborated motions. Coarse-grained elastic-network descriptions are…

Biomolecules · Quantitative Biology 2013-10-17 Yves Dehouck , Alexander S. Mikhailov

The protein-protein interaction (PPI) network provides an overview of the complex biological reactions vital to an organism's metabolism and survival. Even though in the past PPI network were compared across organisms in detail, there has…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Long-Huei Chen , Mohana Prasad Sathya Moorthy , Pratyaksh Sharma

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

Suppose an experiment is conducted on pairs of objects with outcome responses a continuous variable measuring the interactions among the pairs. Furthermore, assume the response variable is hard to measure numerically but easy to be coded…

Methodology · Statistics 2015-05-11 Abdul-Hamid Al-Ibrahim

Computational protein design has a wide variety of applications. Despite its remarkable success, designing a protein for a given structure and function is still a challenging task. On the other hand, the number of solved protein structures…

Quantitative Methods · Quantitative Biology 2018-04-26 Jingxue Wang , Huali Cao , John Z. H. Zhang , Yifei Qi

In this paper, a new method for PPI (proteinprotein interaction) prediction is proposed. In PPI prediction, a reliable and sufficient number of training samples is not available, but a large number of unlabeled samples is in hand. In the…

Machine Learning · Computer Science 2016-07-19 Amir Ahooye Atashin , Parsa Bagherzadeh , Kamaledin Ghiasi-Shirazi

Despite recent advances in protein-ligand structure prediction, deep learning methods remain limited in their ability to accurately predict binding affinities, particularly for novel protein targets dissimilar from the training set. In…

Quantitative Methods · Quantitative Biology 2025-12-04 Michael Brocidiacono , James Wellnitz , Konstantin I. Popov , Alexander Tropsha

We propose a novel method for the determination of the effective interaction potential between the amino acids of a protein. The strategy is based on the combination of a new optimization procedure and a geometrical argument, which also…

Soft Condensed Matter · Physics 2009-10-31 Jort van Mourik , Cecilia Clementi , Amos Maritan , Flavio Seno , J. R. Banavar

Protein-RNA interactions are of vital importance to a variety of cellular activities. Both experimental and computational techniques have been developed to study the interactions. Due to the limitation of the previous database, especially…

Biomolecules · Quantitative Biology 2021-11-24 Junkang Wei , Siyuan Chen , Licheng Zong , Xin Gao , Yu Li

The binding between proteins and ligands plays a crucial role in the realm of drug discovery. Previous deep learning approaches have shown promising results over traditional computationally intensive methods, but resulting in poor…

Biomolecules · Quantitative Biology 2023-11-29 Shikun Feng , Minghao Li , Yinjun Jia , Weiying Ma , Yanyan Lan

Gene and protein networks are very important to model complex large-scale systems in molecular biology. Inferring or reverseengineering such networks can be defined as the process of identifying gene/protein interactions from experimental…

Machine Learning · Computer Science 2017-03-10 Stefano Beretta , Mauro Castelli , Ivo Goncalves , Ivan Merelli , Daniele Ramazzotti

An important problem in the field of bioinformatics is to identify interactive effects among profiled variables for outcome prediction. In this paper, a logistic regression model with pairwise interactions among a set of binary covariates…

Artificial Intelligence · Computer Science 2016-12-30 Easton Li Xu , Xiaoning Qian , Tie Liu , Shuguang Cui

Understanding consumer preferences is essential to product design and predicting market response to these new products. Choice-based conjoint analysis is widely used to model user preferences using their choices in surveys. However,…

Automated identification of protein conformational states from simulation of an ensemble of structures is a hard problem because it requires teaching a computer to recognize shapes. We adapt the naive Bayes classifier from the machine…

Computational Physics · Physics 2020-12-02 David M. Rogers

Pre-trained protein models (PTPMs) represent a protein with one fixed embedding and thus are not capable for diverse tasks. For example, protein structures can shift, namely protein folding, between several conformations in various…

Artificial Intelligence · Computer Science 2022-02-08 Qiang Zhang , Zeyuan Wang , Yuqiang Han , Haoran Yu , Xurui Jin , Huajun Chen

Self-avoiding random walks were performed on protein residue networks. Compared with protein residue networks with randomized links, the probability of a walk being successful is lower and the length of successful walks shorter in…

Molecular Networks · Quantitative Biology 2013-06-11 Susan Khor

Statistical analysis of protein-protein interactions shows anomalously high frequency of homodimers [Ispolatov, I., et al. (2005) Nucleic Acids Res 33, 3629-35]. Furthermore, recent findings [Wright, C.F., et al. (2005) Nature 438, 878-81]…

Biomolecules · Quantitative Biology 2007-05-23 D. B. Lyjatsky , E. I. Shakhnovich

Characterizing interactions between drugs is important to avoid potentially harmful combinations, to reduce off-target effects of treatments and to fight antibiotic resistant pathogens, among others. Here we present a network inference…

Molecular Networks · Quantitative Biology 2014-11-07 Roger Guimera , Marta Sales-Pardo

The analysis of correlations of amino acid occurrences in globular proteins has led to the development of statistical tools that can identify native contacts -- portions of the chains that come to close distance in folded structural…

Biomolecules · Quantitative Biology 2014-07-28 Rocío Espada , R. Gonzalo Parra , Thierry Mora , Aleksandra M. Walczak , Diego Ferreiro