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Engineering molecular systems that exhibit complex behavior requires the design of kinetic barriers. For example, an effective catalytic pathway must have a large barrier when the catalyst is absent. While programming such energy barriers…

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Understanding the intricate interplay among sequence, structure, and function remains a fundamental challenge in proteomics. The sequence-structure-function paradigm posits that biological roles are governed by the tertiary geometric…

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Protein-nucleic acid interactions play a very important role in a variety of biological activities. Accurate identification of nucleic acid-binding residues is a critical step in understanding the interaction mechanisms. Although many…

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Fine-tuning Pre-trained protein language models (PLMs) has emerged as a prominent strategy for enhancing downstream prediction tasks, often outperforming traditional supervised learning approaches. As a widely applied powerful technique in…

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We present a re-parameterization of vector autoregressive moving average (VARMA) models that allows estimation of parameters under the constraints of causality and invertibility. The parameter constraints associated with a causal invertible…

Statistics Theory · Mathematics 2014-06-19 Anindya Roy , Tucker S. McElroy , Peter Linton

We propose an energy-based model (EBM) of protein conformations that operates at atomic scale. The model is trained solely on crystallized protein data. By contrast, existing approaches for scoring conformations use energy functions that…

Machine Learning · Computer Science 2020-04-29 Yilun Du , Joshua Meier , Jerry Ma , Rob Fergus , Alexander Rives

Post-translational modifications (PTMs) form a combinatorial "code" that regulates protein function, yet deciphering this code - linking modified sites to their catalytic enzymes - remains a central unsolved problem in understanding…

Computational Engineering, Finance, and Science · Computer Science 2025-10-28 Jingjie Zhang , Hanqun Cao , Zijun Gao , Yu Wang , Shaoning Li , Jun Xu , Cheng Tan , Jun Zhu , Chang-Yu Hsieh , Chunbin Gu , Pheng Ann Heng

Minimum energy path (MEP) search is a vital but often very time-consuming method to predict the transition states of versatile dynamic processes in chemistry, physics, and materials science. In this study, we reveal that the chemical bond…

Materials Science · Physics 2023-07-18 Hongsheng Cai , Guoyuan Liu , Peiqi Qiu , Guangfu Luo

A novel energy landscape model, ELM, for proteins recently explained a collection of incoherent, elastic neutron scattering data from proteins. The ELM of proteins considers the elastic response of the proton and its environment to the…

Biological Physics · Physics 2018-01-08 Robert D. Young

Proofreading/editing in protein synthesis is essential for accurate translation of information from the genetic code. In this article we present a theoretical investigation of efficiency of a kinetic proofreading mechanism that employs…

Biomolecules · Quantitative Biology 2015-06-15 Mantu Santra , Biman Bagchi

Any organism is embedded in an environment that changes over time. The timescale for and statistics of environmental change, the precision with which the organism can detect its environment, and the costs and benefits of particular protein…

Quantitative Methods · Quantitative Biology 2023-07-19 David A. Sivak , Matt Thomson

A goal in the kinetic characterization of a macromolecular system is the description of its slow relaxation processes, involving (i) identification of the structural changes involved in these processes, and (ii) estimation of the rates or…

Chemical Physics · Physics 2015-06-15 Guillermo Perez-Hernandez , Fabian Paul , Toni Giorgino , Gianni de Fabritiis , Frank Noé

The rate-limiting step of some enzymatic reactions is a physical step, i.e. diffusion. The efficiency of such reactions can be improved through an increase in the arrival rate of the substrate molecules, e.g. by a directed passage of…

Biological Physics · Physics 2007-05-23 Mehrdad Ghaemi , Nasrollah Rezaei-Ghaleh , Mohammad-Nabi Sarbolouki

The rapid progress of multimodal large language models (MLLMs) calls for more reliable evaluation protocols. Existing static benchmarks suffer from the potential risk of data contamination and saturation, leading to inflated or misleading…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Junzhe Zhang , Huixuan Zhang , Xiaojun Wan

To develop and investigate detailed mathematical models of cellular metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, explicit…

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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

Drug resistance is a major threat to the global health and a significant concern throughout the clinical treatment of diseases and drug development. The mutation in proteins that is related to drug binding is a common cause for adaptive…

Quantitative Methods · Quantitative Biology 2022-05-18 Ziyi Yang , Zhaofeng Ye , Yijia Xiao , Changyu Hsieh , Shengyu Zhang

Protein mutations can have profound effects on biological function, making accurate prediction of property changes critical for drug discovery, protein engineering, and precision medicine. Current approaches rely on fine-tuning…

Machine Learning · Computer Science 2025-10-27 Srivathsan Badrinarayanan , Yue Su , Janghoon Ock , Alan Pham , Sanya Ahuja , Amir Barati Farimani

Biocatalysis is a promising approach to sustainably synthesize pharmaceuticals, complex natural products, and commodity chemicals at scale. However, the adoption of biocatalysis is limited by our ability to select enzymes that will catalyze…

Biomolecules · Quantitative Biology 2022-04-06 Samuel Goldman , Ria Das , Kevin K. Yang , Connor W. Coley

Energy-based models (EBMs) provide a powerful and flexible way of learning a joint probability distribution over data by constructing an energy surface. This energy surface enables insight extraction and conditional sampling. We apply EBMs…

Plasma Physics · Physics 2026-05-12 Phil Travis , Troy Carter