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This article introduces a novel binary representation of the canonical genetic code based on both the structural similarities of the nucleotides, as well as the physicochemical properties of the encoded amino acids. Each of the four mRNA…

Biological Physics · Physics 2017-03-27 Louis R. Nemzer

Neuromorphic systems or dedicated hardware for neuromorphic computing is getting popular with the advancement in research on different device materials for synapses, especially in crossbar architecture and also algorithms specific or…

Neural and Evolutionary Computing · Computer Science 2019-01-03 Roshan Gopalakrishnan , Ashish Jith Sreejith Kumar , Yansong Chua

Coarse-grained models can be of great help to address the problem of structure prediction in nucleic acids. On one hand they can make the prediction more efficient, while on the other hand, they can also help to identify the essential…

Biological Physics · Physics 2020-05-05 Simón Poblete , Sandro Bottaro , Giovanni Bussi

The limits of molecular dynamics (MD) simulations of macromolecules are steadily pushed forward by the relentless developments of computer architectures and algorithms. This explosion in the number and extent (in size and time) of MD…

Galvanic replacement reactions on metal nanoparticles are often used for the preparation of hollow nanostructures with tunable porosity and chemical composition, leading to tailored optical and catalytic properties. However, the precise…

The pathway is a biological term that refers to a series of interactions between molecules in a cell that causes a certain product or a change in the cell. Pathway analysis is a powerful method for gene expression analysis. Through pathway…

Data Structures and Algorithms · Computer Science 2022-01-11 Lingran Xiao , Yanfei Wang , Shiying Li , Lingxi Chen , Shuaicheng Li

Understanding material composition-structure-function relationships is of critical importance for the design and discovery of novel functional materials. While most such studies focus on individual materials, we conducted a global mapping…

Materials Science · Physics 2023-02-14 Qinyang Li , Rongzhi Dong , Nihang Fu , Sadman Sadeed Omee , Lai Wei , Jianjun Hu

Chemical reactions can be understood as transformations of multigraphs (molecules) that preserve vertex labels (atoms) and degrees (sums of bonding and non-bonding electrons), thereby implying the atom-atom map of a reaction. The…

Combinatorics · Mathematics 2023-11-23 Christoph Flamm , Stefan Müller , Peter F. Stadler

In drug discovery, knowledge of the graph structure of chemical compounds is essential. Many thousands of scientific articles in chemistry and pharmaceutical sciences have investigated chemical compounds, but in cases the details of the…

Machine Learning · Statistics 2020-09-16 Martijn Oldenhof , Adam Arany , Yves Moreau , Jaak Simm

To comprehend the multipartite organization of large-scale biological and social systems, we introduce a new information theoretic approach that reveals community structure in weighted and directed networks. The method decomposes a network…

Physics and Society · Physics 2008-02-13 M. Rosvall , C. T. Bergstrom

A novel framework has recently been proposed for designing the molecular structure of chemical compounds with a desired chemical property using both artificial neural networks and mixed integer linear programming. In the framework, a…

Machine Learning · Computer Science 2021-08-24 Naveed Ahmed Azam , Jianshen Zhu , Kazuya Haraguchi , Liang Zhao , Hiroshi Nagamochi , Tatsuya Akutsu

In this work, we present an application of Locally Interpretable Machine-Agnostic Explanations to 2-D chemical structures. Using this framework we are able to provide a structural interpretation for an existing black-box model for…

Machine Learning · Statistics 2016-11-23 Leanne S. Whitmore , Anthe George , Corey M. Hudson

Compound-protein pairs dominate FDA-approved drug-target pairs and the prediction of compound-protein affinity and contact (CPAC) could help accelerate drug discovery. In this study we consider proteins as multi-modal data including 1D…

Biomolecules · Quantitative Biology 2020-12-02 Yuning You , Yang Shen

In this PhD thesis, a novel method to determine protein structures using chemical shifts is presented.

Chemical Physics · Physics 2014-05-15 Anders S. Christensen

One-dimensional nuclear magnetic resonance (NMR) spectroscopy is essential for molecular structure elucidation in organic synthesis, drug discovery, natural product characterization, and metabolomics, yet its interpretation remains heavily…

The first step in the construction of a regression model or a data-driven analysis, aiming to predict or elucidate the relationship between the atomic scale structure of matter and its properties, involves transforming the Cartesian…

We compare two recently proposed methods for the characterization of phase transitions in small systems. The usefulness of these techniques is evaluated for the case of structural transition in alanine-based peptides.

Statistical Mechanics · Physics 2007-05-23 Nelson A. Alves , U. H. E. Hansmann , Y. Peng

Designing molecular structures with desired chemical properties is an essential task in drug discovery and material design. However, finding molecules with the optimized desired properties is still a challenging task due to combinatorial…

Biomolecules · Quantitative Biology 2023-02-02 Masatsugu Yamada , Mahito Sugiyama

When nanoparticles (NPs) are introduced into a biological solution, layers of biomolecules form on their surface, creating a corona. Understanding how the structure of the protein evolves into the corona is essential for evaluating the…

Here we focus on the challenge of verifying the correctness of molecular implementations of abstract chemical reaction networks, where operation in a well-mixed "soup" of molecules is stochastic, asynchronous, concurrent, and often involves…

Computational Engineering, Finance, and Science · Computer Science 2019-10-01 Seung Woo Shin , Chris Thachuk , Erik Winfree