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The expression of one gene might be regulated by its corresponding protein, which is called autoregulation. Although gene regulation is a central topic in biology, autoregulation is much less studied. In general, it is extremely difficult…

Molecular Networks · Quantitative Biology 2023-03-31 Yue Wang , Siqi He

Foundation models are powerful yet often opaque in their decision-making. A topic of continued interest in both neuroscience and artificial intelligence is whether some neurons behave like grandmother cells, i.e., neurons that are…

Machine Learning · Computer Science 2026-01-08 Ricardo Knauer , Erik Rodner

Molecular noise in gene regulatory networks has two intrinsic components, one part being due to fluctuations caused by the birth and death of protein or mRNA molecules which are often present in small numbers and the other part arising from…

Molecular Networks · Quantitative Biology 2015-11-17 Davit A. Potoyan , Peter G. Wolynes

Transcription factor proteins bind specific DNA sequences to control the expression of genes. They contain DNA binding domains which belong to several super-families, each with a specific mechanism of DNA binding. The total number of…

Biomolecules · Quantitative Biology 2010-07-27 Shalev Itzkovitz , Tsvi Tlusty , Uri Alon

A single gene, regulating its own expression via a positive feedback loop, constitutes a common motif in gene regulatory networks and signalling cascades. Recent experiments on the development of competence in the bacterial population…

Quantitative Methods · Quantitative Biology 2007-05-23 Rajesh Karmakar , Indrani Bose

This work illustrates potentials for recognition within {\em ad hoc} sensor networks if their nodes possess individual inter-related biologically inspired genetic codes. The work takes ideas from natural immune systems protecting organisms…

Cryptography and Security · Computer Science 2009-12-31 Reinert Korsnes , Knut Ovsthus

The application of deep learning methods, particularly foundation models, in biological research has surged in recent years. These models can be text-based or trained on underlying biological data, especially omics data of various types.…

Artificial Intelligence · Computer Science 2024-12-06 Yoav Kan-Tor , Michael Morris Danziger , Eden Zohar , Matan Ninio , Yishai Shimoni

Discovering genes with similar functions across diverse biomedical contexts poses a significant challenge in gene representation learning due to data heterogeneity. In this study, we resolve this problem by introducing a novel model called…

Machine Learning · Computer Science 2023-10-05 Tianyu Liu , Yuge Wang , Rex Ying , Hongyu Zhao

Understanding cell fate selection remains a central challenge in developmental biology. We present a class of simple yet biologically-motivated mathematical models for cell differentiation that generically generate oscillations and hence…

Dynamical Systems · Mathematics 2021-10-08 Saeed Farjami , Karen Camargo Sosa , Jonathan H. P. Dawes , Robert N. Kelsh , Andrea Rocco

Phenotypic variation is a hallmark of cellular physiology. Metabolic heterogeneity, in particular, underpins single-cell phenomena such as microbial drug tolerance and growth variability. Much research has focussed on transcriptomic and…

Molecular Networks · Quantitative Biology 2019-01-31 Mona K. Tonn , Philipp Thomas , Mauricio Barahona , Diego A Oyarzún

The regularized random forest (RRF) was recently proposed for feature selection by building only one ensemble. In RRF the features are evaluated on a part of the training data at each tree node. We derive an upper bound for the number of…

Machine Learning · Computer Science 2013-06-21 Houtao Deng , George Runger

Exposure bias describes the phenomenon that a language model trained under the teacher forcing schema may perform poorly at the inference stage when its predictions are conditioned on its previous predictions unseen from the training…

Computation and Language · Computer Science 2020-04-02 Yifan Xu , Kening Zhang , Haoyu Dong , Yuezhou Sun , Wenlong Zhao , Zhuowen Tu

We present a novel classification-based method for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple organisms such as Saccharomyces cerevisiae, we can learn a decision rule for…

Quantitative Methods · Quantitative Biology 2007-05-23 Manuel Middendorf , Anshul Kundaje , Chris Wiggins , Yoav Freund , Christina Leslie

Motivation: The regulation of gene expression during tissue development is extremely complex. One of the key regulatory mechanisms of gene expression involves the recognition of regulatory motifs by various proteins in the promoter regions…

We present a novel machine learning architecture for classification suggested by experiments on olfactory systems. The network separates input stimuli, represented as spatially distinct currents, via winnerless competition---a process based…

Biological Physics · Physics 2020-06-18 Jason A. Platt , Anna Miller , Lawson Fuller , Henry D. I. Abarbanel

The well-known issue of reconstructing regulatory networks from gene expression measurements has been somewhat disrupted by the emergence and rapid development of single-cell data. Indeed, the traditional way of seeing a gene regulatory…

Molecular Networks · Quantitative Biology 2021-10-01 Ulysse Herbach

Multicellular organisms comprise a diverse collection of stable tissues built from different cell types. It remains unclear how large numbers of interacting cells can precisely coordinate their gene expression during tissue…

Biological Physics · Physics 2022-10-31 Matthew Smart , Anton Zilman

Biological and machine pattern recognition systems face a common challenge: Given sensory data about an unknown object, classify the object by comparing the sensory data with a library of internal representations stored in memory. In many…

Information Theory · Computer Science 2007-07-13 M. Brandon Westover , Joseph A. O'Sullivan

Gene regulation relies on the specificity of transcription factor (TF) - DNA interactions. In equilibrium, limited specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to noncognate…

Molecular Networks · Quantitative Biology 2016-10-31 Tamar Friedlander , Roshan Prizak , Călin C. Guet , Nicholas H. Barton , Gašper Tkačik

When a population inhabits an inhomogeneous environment, the fitness value of traits can vary with the position in the environment. Gene flow caused by random mating can nevertheless prevent that a sexually reproducing population splits…

Populations and Evolution · Quantitative Biology 2011-05-05 Susanne Schindler , Olaf Breidbach , Juergen Jost