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Recent research has extended methods from the fields of thermodynamics and statistical mechanics into other disciplines. Most notably, one recent work creates a unified theoretical framework to understand evolutionary biology, machine…

Populations and Evolution · Quantitative Biology 2024-05-22 Daniel Sadasivan , Cole Cantu , Cecilia Marsh , Andrew Graham

The problem addressed here is that of simultaneous treatment of several gene expression datasets, possibly collected under different experimental conditions and/or platforms. Using robust statistics, a large scale statistical analysis has…

Methodology · Statistics 2014-10-10 Bernard Ycart , Konstantina Charmpi , Sophie Rousseaux , Jean-Jacques Fournié

This paper develops a theory for characterisation of DNA sequences based on their measure representation. The measures are shown to be random cascades generated by an infinitely divisible distribution. This probability distribution is…

Biological Physics · Physics 2009-11-07 Vo Anh , Ka-Sing Lau , Zu-Guo Yu

Microarray data are often used to determine which genes are differentially expressed between groups, for example, between treatment and control groups. There are methods of determining which genes have a high probability of differential…

Quantitative Methods · Quantitative Biology 2007-05-23 David R. Bickel

A general theoretical framework is put forth to organize and understand various observed phenomena and mathematical relationships in the field of molecular biology. By modeling each cell in eukaryotic organisms as a processor having a…

Other Quantitative Biology · Quantitative Biology 2013-12-18 Barry D. Jacobson

In microarray experiments, it is often of interest to identify genes which have a pre-specified gene expression profile with respect to time. Methods available in the literature are, however, typically not stringent enough in identifying…

Applications · Statistics 2009-01-18 J. Tuke , G. F. V. Glonek , P. J. Solomon

Assessing the correctness of genome assemblies is an important step in any genome project. Several methods exist, but most are computationally intensive and, in some cases, inappropriate. Here I present baa.pl, a fast and easy-to-use…

Genomics · Quantitative Biology 2014-02-10 Joseph F. Ryan

Understanding the relationship between genomic variation and variation in phenotypes for quantitative traits such as physiology, yield, fitness or behavior, will provide important insights for both predicting adaptive evolution and for…

Networks of genetic expression can be modelled by hypergraphs with the additional structure that real coefficients are given to each vertex-edge incidence. The spectra, i.e. the multiset of the eigenvalues, of such hypergraphs, are known to…

Molecular Networks · Quantitative Biology 2021-09-24 Raffaella Mulas , Michael J. Casey

For the vast majority of genes in sequenced genomes, there is limited understanding of how they are regulated. Without such knowledge, it is not possible to perform a quantitative theory-experiment dialogue on how such genes give rise to…

Genomics · Quantitative Biology 2024-06-07 Rosalind Wenshan Pan , Tom Roeschinger , Kian Faizi , Hernan Garcia , Rob Phillips

In this paper we suggest that, under suitable conditions, supervised learning can provide the basis to formulate at the microscopic level quantitative questions on the phenotype structure of multicellular organisms. The problem of…

Molecular Networks · Quantitative Biology 2012-06-14 D. Napoletani , E. Petricoin , D. C. Struppa

This study demonstrates that generative large language models can be utilized in a more flexible manner for DNA sequence analysis and classification tasks compared to traditional transformer encoder-based models. While recent encoder-based…

Computation and Language · Computer Science 2025-03-07 Hyunwoo Yoo

Proteins are macromolecules that mediate a significant fraction of the cellular processes that underlie life. An important task in bioengineering is designing proteins with specific 3D structures and chemical properties which enable…

Quantitative Methods · Quantitative Biology 2022-05-31 Namrata Anand , Tudor Achim

In many longitudinal microarray studies, the gene expression levels in a random sample are observed repeatedly over time under two or more conditions. The resulting time courses are generally very short, high-dimensional, and may have…

Applications · Statistics 2013-02-26 Maurice Berk , Cheryl Hemingway , Michael Levin , Giovanni Montana

Plant breeding programs use data obtained from multi-environment selection experiments to produce improved varieties with the ultimate aim of maintaining high levels of genetic gain. Selection accuracy can be improved with the use of…

Methodology · Statistics 2026-05-13 Brian R Cullis , Alison B Smith , David GD Hughes , David Butler

Researchers spend a great deal of time reading research papers. Keshav (2012) provides a three-pass method to researchers to improve their reading skills. This article extends Keshav's method for reading a research compendium. Research…

General Literature · Computer Science 2018-06-26 Daniel Nüst , Carl Boettiger , Ben Marwick

By integrating heterogeneous functional genomic datasets, we have developed a new framework for detecting combinatorial control of gene expression, which includes estimating transcription factor activities using a singular value…

Quantitative Methods · Quantitative Biology 2010-10-07 Junbai Wang

Gene expression datasets offer insights into gene regulation mechanisms, biochemical pathways, and cellular functions. Additionally, comparing gene expression profiles between disease and control patients can deepen the understanding of…

Machine Learning · Computer Science 2025-03-27 Rita T. Sousa , Heiko Paulheim

Numerous transcription factors self-assemble into different order oligomeric species in a way that is actively regulated by the cell. Until now, no general functional role has been identified for this widespread process. Here we capture the…

Molecular Networks · Quantitative Biology 2011-05-26 Jose M. G. Vilar , Leonor Saiz

This paper develops a Bayesian graphical model for fusing disparate types of count data. The motivating application is the study of bacterial communities from diverse high dimensional features, in this case transcripts, collected from…