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Extracting associations that recur across multiple studies while controlling the false discovery rate is a fundamental challenge. Here, we consider an extension of Efron's single-study two-groups model to allow joint analysis of multiple…

Methodology · Statistics 2019-01-14 David Amar , Ron Shamir , Daniel Yekutieli

This paper proposes a new mathematical framework that can be applied to biological problems such as analysis of the structures of proteins and protein complexes. In particular, it gives a new method for encoding the three-dimensional…

Combinatorics · Mathematics 2007-05-23 Naoto Morikawa

The mathematical concept of q-deformations, in particular the one of qnumbers, is used to study the genetic code(s). After considering two kinds of q-numbers, for comparison, a phenomenological classification scheme of the genetic code…

Other Quantitative Biology · Quantitative Biology 2016-07-26 Tidjani Negadi

The usage frequencies for codons belonging to quartets are analized, over the whole exonic region, for 92 biological species. Correlation is put into evidence, between the usage frequencies of synonymous codons with third nucleotide A and C…

Other Quantitative Biology · Quantitative Biology 2016-09-09 Diego Cocurullo , Antonino Sciarrino

Building on recent development by Padakandla and Pradhan, and by Lim, Feng, Pastore, Nazer, and Gastpar, this paper studies the potential of structured nested coset coding as a complete replacement for random coding in network information…

Information Theory · Computer Science 2018-01-24 Pinar Sen , Young-Han Kim

We investigated the error-minimization properties of putative primordial codes that consisted of 16 supercodons, with the third base being completely redundant, using a previously derived cost function and the error minimization percentage…

Genomics · Quantitative Biology 2009-08-26 Artem S. Novozhilov , Eugene V. Koonin

The classification of amino acids and their sequence analysis plays a vital role in life sciences and is a challenging task. This article uses and compares state-of-the-art deep learning models like convolution neural networks (CNN), long…

Biomolecules · Quantitative Biology 2022-07-26 Sarwar Khan , Faisal Ghaffar , Imad Ali , Qazi Mazhar

The sequence of amino acid monomers in the primary structure of a protein is decided by the corresponding sequence of codons (triplets of nucleic acid monomers) on the template messenger RNA (mRNA). The polymerization of a protein, by…

Biological Physics · Physics 2017-06-02 Annwesha Dutta , Debashish Chowdhury

Motivation: The design of enzymes is as challenging as it is consequential for making chemical synthesis in medical and industrial applications more efficient, cost-effective and environmentally friendly. While several aspects of this…

Motivation: The consistent amount of different types of omics data requires novel methods of analysis and data integration. In this work we describe Regression2Net, a computational approach to analyse gene expression and methylation…

Computational Engineering, Finance, and Science · Computer Science 2015-07-06 Francesco Gadaleta , Kyrylo Bessonov

What are proteins made from, as the working parts of the living cells protein machines? To answer this question, we need a technology to disassemble proteins onto elementary func-tional details and to prepare lumped description of such…

Biomolecules · Quantitative Biology 2007-11-05 A. N. Gorban , M. Kudryashev , T. Popova

The ultimate secret of all lives on earth is hidden in their genomes -- a totality of DNA sequences. We currently know the whole genome sequence of many organisms, while our understanding of the genome architecture on a systematic level…

Genomics · Quantitative Biology 2020-09-08 Yanying Wu

This work is concerned with the development of a well-founded, theoretically justified, and least complicated metric for the classification of proteins with reference to enzymes. As the signature of an enzyme family, a catalytic domain is…

Genomics · Quantitative Biology 2007-08-17 Ashok Palaniappan

Simulating generic quantum states and dynamics is practically intractable using classical computers. However, certain special classes -- namely Clifford and matchgate circuits -- permit efficient computation. They provide invaluable tools…

Quantum Physics · Physics 2025-05-13 Byungmin Kang , Chen Zhao , Zhengwei Liu , Xun Gao , Soonwon Choi

This paper is dealing with DNA cyclic codes which play an important role in DNA computing and have attracted a particular attention in the literature. Firstly, we introduce a new family of DNA cyclic codes over the ring…

Information Theory · Computer Science 2015-05-26 Nabil Bennenni , Kenza Guenda , Sihem Mesnager

Recently, Graph Convolutional Networks (GCNs) have proven to be a powerful mean for Computer Aided Diagnosis (CADx). This approach requires building a population graph to aggregate structural information, where the graph adjacency matrix…

Artificial Intelligence · Computer Science 2021-06-17 Hao Chen , Fuzhen Zhuang , Li Xiao , Ling Ma , Haiyan Liu , Ruifang Zhang , Huiqin Jiang , Qing He

Advances in classical machine learning and single-cell technologies have paved the way to understand interactions between disease cells and tumor microenvironments to accelerate therapeutic discovery. However, challenges in these machine…

Quantum Physics · Physics 2023-10-18 Anupama Ray , Dhiraj Madan , Srushti Patil , Maria Anna Rapsomaniki , Pushpak Pati

Genes carry the instructions for making proteins that are found in a cell as a specific sequence of nucleotides that are found in DNA molecules. But, the regions of these genes that code for proteins may occupy only a small region of the…

Computational Engineering, Finance, and Science · Computer Science 2014-01-28 Pokkuluri Kiran Sree , Inampudi Ramesh Babu

A new algorithm to compute cylindrical algebraic decompositions (CADs) is presented, building on two recent advances. Firstly, the output is truth table invariant (a TTICAD) meaning given formulae have constant truth value on each cell of…

Symbolic Computation · Computer Science 2014-09-04 R. Bradford , C. Chen , J. H. Davenport , M. England , M. Moreno Maza , D. Wilson

In this study, we intend to solve a mutual information problem in interacting molecules of any type, such as proteins, nucleic acids, and small molecules. Using machine learning techniques, we accurately predict pairwise interactions, which…

Machine Learning · Statistics 2016-01-28 Andrew Schaumberg , Angela Yu , Tatsuhiro Koshi , Xiaochan Zong , Santoshkalyan Rayadhurgam
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