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Mixture proportion estimation (MPE) is the problem of estimating the weight of a component distribution in a mixture, given samples from the mixture and component. This problem constitutes a key part in many "weakly supervised learning"…

Machine Learning · Computer Science 2016-06-01 Harish G. Ramaswamy , Clayton Scott , Ambuj Tewari

Hydrogen bonds and other non-covalent interactions play a crucial role in maintaining the structural integrity and functionality of biological macromolecules such as proteins and nucleic acids. Accurate identification and analysis of these…

Chemical Physics · Physics 2026-02-23 Abhishek Tiwari

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…

The key finding in the DNA double helix model is the specific pairing or binding between nucleotides A-T and C-G, and the pairing rules are the molecule basis of genetic code. Unfortunately, no such rules have been discovered for proteins.…

Biomolecules · Quantitative Biology 2017-02-28 Yuhong Wang , Junzhou Huang , Wei Li , Sheng Wang , Chuanfan Ding

Proteins are the basic building blocks of life. They usually perform functions by folding to a particular structure. Understanding the folding process could help the researchers to understand the functions of proteins and could also help to…

Computational Engineering, Finance, and Science · Computer Science 2015-10-21 Jianzhu Ma

Mixture models have received a great deal of attention in statistics due to the wide range of applications found in recent years. This paper discusses a finite mixture model of Birnbaum- Saunders distributions with G components, as an…

Methodology · Statistics 2017-08-03 Luis Benites , Rocío Maehara , Filidor Vilca , Fernando Marmolejo-Ramos

We propose an application of molecular information theory to analyze the folding of single domain proteins. We analyze results from various areas of protein science, such as sequence-based potentials, reduced amino acid alphabets, backbone…

Biomolecules · Quantitative Biology 2022-06-30 Ignacio E. Sánchez , Ezequiel A. Galpern , Martín M. Garibaldi , Diego U. Ferreiro

In systems biology, it is common to measure biochemical entities at different levels of the same biological system. One of the central problems for the data fusion of such data sets is the heterogeneity of the data. This thesis discusses…

Genomics · Quantitative Biology 2019-08-27 Yipeng Song

Mixture distributions are a workhorse model for multimodal data in information theory, signal processing, and machine learning. Yet even when each component density is simple, the differential entropy of the mixture is notoriously hard to…

Information Theory · Computer Science 2026-02-18 Namyoon Lee

If a deuterated molecule containing strong intramolecular hydrogen bonds is placed in a hydrogenated solvent it may preferentially exchange deuterium for hydrogen. This preference is due to the difference between the vibrational zero-point…

Chemical Physics · Physics 2015-08-07 Ross H. McKenzie , Bijyalaxmi Athokpam , Sai Ramesh

Membrane bending is an extensively studied problem from both modeling and experimental perspectives because of the wide implications of curvature generation in cell biology. Many of the curvature generating aspects in membranes can be…

Soft Condensed Matter · Physics 2021-07-21 Arijit Mahapatra , David Saintillan , Padmini Rangamani

Two phase solid-fluid mixture models are ubiquitous in biological applications. For instance, models for growth of tissues and biofilms combine time dependent and quasi-stationary boundary value problems set in domains whose boundary moves…

Analysis of PDEs · Mathematics 2024-01-17 Ana Carpio , Gema Duro

Specific protein-protein interactions are crucial in the cell, both to ensure the formation and stability of multi-protein complexes, and to enable signal transduction in various pathways. Functional interactions between proteins result in…

Biological Physics · Physics 2016-11-21 Anne-Florence Bitbol , Robert S. Dwyer , Lucy J. Colwell , Ned S. Wingreen

Food webs are complex ecological networks whose structure is both ecologically and statistically constrained, with many network properties being correlated with each other. Despite the recognition of these invariable relationships in food…

Quantitative Methods · Quantitative Biology 2023-01-18 Francis Banville , Dominique Gravel , Timothée Poisot

The structure and function of biological molecules are strongly influenced by the water and dissolved ions that surround them. This aqueous solution (solvent) exerts significant electrostatic forces in response to the biomolecule's…

Numerical Analysis · Mathematics 2015-12-29 Matthew G. Knepley , Jaydeep P. Bardhan

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

Binomial data with unknown sizes often appear in biological and medical sciences and are usually overdispersed. All previous methods used parametric models and only considered overdispersion due to the variation of sizes. The proposed…

Statistics Theory · Mathematics 2007-06-13 Wei Zhang

Rigidity analysis using the "pebble game" has been applied to protein crystal structures to obtain information on protein folding, assembly and t he structure-function relationship. However, previous work using this technique has not made…

Biomolecules · Quantitative Biology 2015-05-13 SA Wells , JE Jimenez-Roldan , RA Römer

The concept of chemical bonding can ultimately be seen as a rationalization of the recurring structural patterns observed in molecules and solids. Chemical intuition is nothing but the ability to recognize and predict such patterns, and how…

Chemical Physics · Physics 2014-11-14 Piero Gasparotto , Michele Ceriotti

Multivariate normal mixtures provide a flexible model for high-dimensional data. They are widely used in statistical genetics, statistical finance, and other disciplines. Due to the unboundedness of the likelihood function, classical…

Statistics Theory · Mathematics 2008-05-27 Jiahua Chen , Xianming Tan