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We propose a methodology for the identification of transcription factors involved in the deregulation of genes in tumoral cells. This strategy is based on the inference of a reference gene regulatory network that connects transcription…

Molecular Networks · Quantitative Biology 2020-04-20 Magali Champion , Julien Chiquet , Pierre Neuvial , Mohamed Elati , François Radvanyi , Etienne Birmelé

The conventional way of identifying DNA motifs, solely based on match alignment information, is susceptible to a high number of spurious sites. A novel scoring system has been introduced by taking both match and mismatch alignment…

Quantitative Methods · Quantitative Biology 2014-03-03 Jian-Jun Shu , Kian Yan Yong

A Profile Mixture Model is a model of protein evolution, describing sequence data in which sites are assumed to follow many related substitution processes on a single evolutionary tree. The processes depend in part on different amino acid…

Populations and Evolution · Quantitative Biology 2020-07-07 Samaneh Yourdkhani , Elizabeth S. Allman , John A. Rhodes

We study theoretically the in vitro evolution of a DNA sequence by binding to a transcription factor. Using a simple model of protein-DNA binding and available binding constants for the Mnt protein, we perform large-scale, realistic…

Condensed Matter · Physics 2009-11-10 Morten Kloster , Chao Tang

We examine the binding of transcription factors to DNA in terms of an information transfer problem. The input of the noisy channel is the biophysical signal of a factor bound to a DNA site, and the output is a distribution of probable DNA…

Genomics · Quantitative Biology 2015-08-07 Yonatan Savir Jacob Kagan , Tsvi Tlusty

Identification of essential genes is one of the ultimate goals of drug designs. Here we introduce an {\it in silico} method to select essential genes through the microarray assay. We construct a graph of genes, called the gene transcription…

Statistical Mechanics · Physics 2007-05-23 K. Rho , H. Jeong , B. Kahng

Transcription factors (TFs) are regulatory proteins that bind DNA in promoter regions of the genome and either promote or repress gene expression. Here we predict analytically that enhanced homo-oligonucleotide sequence correlations, such…

Biomolecules · Quantitative Biology 2011-11-15 Itamar Sela , David B. Lukatsky

Sequence discovery tools play a central role in several fields of computational biology. In the framework of Transcription Factor binding studies, motif finding algorithms of increasingly high performance are required to process the big…

Quantitative Methods · Quantitative Biology 2014-08-27 Nicolò Colombo , Nikos Vlassis

DNA-binding proteins are a class of proteins which have a specific or general affinity to DNA and include three important components: transcription factors; nucleases, and histones. DNA-binding proteins also perform important roles in many…

Computer Vision and Pattern Recognition · Computer Science 2012-07-12 Sokyna Qatawneh , Afaf Alneaimi , Thamer Rawashdeh , Mmohammad Muhairat , Rami Qahwaji , Stan Ipson

Locating recombination hotspots in genomic data is an important but difficult task. Current methods frequently rely on estimating complicated models at high computational cost. In this paper we develop an extremely fast, scalable method for…

Applications · Statistics 2015-12-08 Jordan Rodu , Shane T. Jensen

DNA is subject to large deformations in a wide range of biological processes. Two key examples illustrate how such deformations influence the readout of the genetic information: the sequestering of eukaryotic genes by nucleosomes, and DNA…

Biomolecules · Quantitative Biology 2015-11-10 Stephanie Johnson , Martin Lindén , Rob Phillips

Strong experimental and theoretical evidence shows that transcription factors and other specific DNA-binding proteins find their sites using a two-mode search: alternating between 3D diffusion through the cell and 1D sliding along the DNA.…

Biomolecules · Quantitative Biology 2008-06-11 Zeba Wunderlich , Leonid A. Mirny

We introduce a new method for finding network motifs: interesting or informative subgraph patterns in a network. Subgraphs are motifs when their frequency in the data is high compared to the expected frequency under a null model. To compute…

Machine Learning · Computer Science 2021-04-19 Peter Bloem , Steven de Rooij

We analyze the convergence rate of a simplified version of a popular Gibbs sampling method used for statistical discovery of gene regulatory binding motifs in DNA sequences. This sampler satisfies a very strong form of ergodicity (uniform).…

Statistics Theory · Mathematics 2013-03-13 Dawn B. Woodard , Jeffrey S. Rosenthal

We describe and solve a discrete persistent chain model of protein binding on DNA, involving an extra sigma_i s at a site i of the DNA. This variable takes the value 1 or 0 depending on whether the site is occupied by a protein or not. In…

Statistical Mechanics · Physics 2015-05-27 Pui-Man Lam , Yi Zhen

From the response to external stimuli to cell division and death, the dynamics of living cells is based on the expression of specific genes at specific times. The decision when to express a gene is implemented by the binding and unbinding…

Molecular Networks · Quantitative Biology 2009-11-13 Johannes Berg

Exploring statistics of locally connected subgraph patterns (also known as network motifs) has helped researchers better understand the structure and function of biological and online social networks (OSNs). Nowadays the massive size of…

Social and Information Networks · Computer Science 2014-03-28 Pinghui Wang , John C. S. Lui , Bruno Ribeiro , Don Towsley , Junzhou Zhao , Xiaohong Guan

The Hill coefficient is often used as a direct measure of the cooperativity of binding processes. It is an essential tool for probing properties of reactions in many biochemical systems. Here we analyze existing experimental data and…

Biological Physics · Physics 2012-08-31 M. Sheinman , Y. Kafri

Protein motifs are conserved fragments occurred frequently in protein sequences. They have significant functions, such as active site of an enzyme. Search and clustering protein sequence motifs are computational intensive. Most existing…

Genomics · Quantitative Biology 2017-01-03 Haifeng Chen , Ting Chen

In explainable artificial intelligence, discriminative feature localization is critical to reveal a blackbox model's decision-making process from raw data to prediction. In this article, we use two real datasets, the MNIST handwritten…

Machine Learning · Statistics 2022-11-21 Ben Dai , Xiaotong Shen , Lin Yee Chen , Chunlin Li , Wei Pan