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RNA polymerase (RNAP) is a mobile molecular workshop that polymerizes a RNA molecule by adding monomeric subunits one by one, while moving step by step on the DNA template itself. Here we develop a theoretical model by incorporating the…

Biological Physics · Physics 2009-06-04 Tripti Tripathi , Prasanjit Prakash , Debashish Chowdhury

Gene regulatory networks typically have low in-degrees, whereby any given gene is regulated by few of the genes in the network. What mechanisms might be responsible for these low in-degrees? Starting with an accepted framework of the…

Molecular Networks · Quantitative Biology 2009-10-22 Z. Burda , A. Krzywicki , O. C. Martin , M. Zagorski

Often in bacterial regulatory networks, small noncoding RNAs (sRNA) interact with several mRNA species. The competition among mRNAs for binding to the same pool of sRNA might lead to crosstalk between the mRNAs. This is similar to the…

Molecular Networks · Quantitative Biology 2019-12-17 Swathi Tej , Sutapa Mukherji

Gene expression analysis aims at identifying the genes able to accurately predict biological parameters like, for example, disease subtyping or progression. While accurate prediction can be achieved by means of many different techniques,…

Methodology · Statistics 2008-09-11 Christine De Mol , Sofia Mosci , Magali Traskine , Alessandro Verri

Formal methods have enabled breakthroughs in many fields, such as in hardware verification, machine learning and biological systems. The key object of interest in systems biology, synthetic biology, and molecular programming is chemical…

Emerging Technologies · Computer Science 2020-08-11 Marko Vasic , David Soloveichik , Sarfraz Khurshid

Protein translation is a multistep process which can be represented as a cascade of biochemical reactions (initiation, ribosome assembly, elongation, etc.), the rate of which can be regulated by small non-coding microRNAs through multiple…

Molecular Networks · Quantitative Biology 2010-03-09 Andrei Zinovyev , Nadya Morozova , Nora Nonne , Emmanuel Barillot , Annick Harel-Bellan , Alexander N. Gorban

Single-cell RNA sequencing (scRNA-seq) has revolutionized our ability to analyze gene expression at the resolution of individual cells, providing unprecedented insights into cellular heterogeneity and complex biological systems. This paper…

Other Quantitative Biology · Quantitative Biology 2024-06-11 Megha Patel , Nimish Magre , Himanshi Motwani , Nik Bear Brown

Regulation of mRNA decay is a critical component of global cellular adaptation to changing environments. The corresponding changes in mRNA lifetimes can be coordinated with changes in mRNA transcription rates to fine-tune gene expression.…

Cell Behavior · Quantitative Biology 2015-05-14 Vlad Elgart , Tao Jia , Rahul Kulkarni

Systemic properties of living cells are the result of molecular dynamics governed by so-called genetic regulatory networks (GRN). These networks capture all possible features of cells and are responsible for the immense levels of adaptation…

Molecular Networks · Quantitative Biology 2015-06-04 Rudolf Hanel , Manfred Pöchacker , Manuel Schölling , Stefan Thurner

RNA can be used as a high-density medium for data storage and transmission; however, an important RNA process -- replication -- is noisy. This paper presents an error analysis for RNA as a data transmission medium, analyzing how deletion…

Emerging Technologies · Computer Science 2016-09-26 Andrew W. Eckford , Taro Furbayashi , Tadashi Nakano

This paper presents our computational methodology using Genetic Algorithms (GA) for exploring the nature of RNA editing. These models are constructed using several genetic editing characteristics that are gleaned from the RNA editing system…

Neural and Evolutionary Computing · Computer Science 2007-05-23 C. Huang , L. M. Rocha

Our work is concerned with the generation and targeted design of RNA, a type of genetic macromolecule that can adopt complex structures which influence their cellular activities and functions. The design of large scale and complex…

Biomolecules · Quantitative Biology 2021-02-02 Zichao Yan , William L. Hamilton , Mathieu Blanchette

Background: Small interfering RNA (siRNA) is a promising therapeutic agent due to its ability to silence disease-related genes via RNA interference. While traditional machine learning and early deep learning methods have made progress in…

Biomolecules · Quantitative Biology 2025-03-07 Wangdan Liao , Weidong Wang

The diversity of expressed genes plays a critical role in cellular specialization, adaptation to environmental changes, and overall cell functionality. This diversity varies dramatically across cell types and is orchestrated by intricate,…

Biological Physics · Physics 2023-11-28 Orr Levy , Shubham Tripathi , Scott D. Pope , Yang Y. Liu , Ruslan Medzhitov

Gene regulatory networks (GRNs) play a crucial role in the control of cellular functions. Numerous methods have been developed to infer GRNs from gene expression data, including mechanism-based approaches, information-based approaches, and…

Molecular Networks · Quantitative Biology 2025-05-16 Xueying Tian , Yash Patel , Yue Wang

Accurately inferring the root causes of disease from sequencing data can improve the discovery of novel therapeutic targets. However, existing root causal inference algorithms require perfectly measured continuous random variables. Single…

Genomics · Quantitative Biology 2023-07-12 Eric V. Strobl

Reconstructing transcriptional regulatory networks is an important task in functional genomics. Data obtained from experiments that perturb genes by knockouts or RNA interference contain useful information for addressing this reconstruction…

Machine Learning · Statistics 2015-06-18 Ali Shojaie , Alexandra Jauhiainen , Michael Kallitsis , George Michailidis

DNA microarrays are a relatively new technology that can simultaneously measure the expression level of thousands of genes. They have become an important tool for a wide variety of biological experiments. One of the most common goals of DNA…

Methodology · Statistics 2013-07-02 Eric Bair

Several studies highlighted the relevance of extrinsic noise in shaping cell decision making and differentiation in molecular networks. Experimental evidences of phenotypic differentiation are given by the presence of bimodal distributions…

Molecular Networks · Quantitative Biology 2017-04-19 Marco Del Giudice , Stefano Bo , Silvia Grigolon , Carla Bosia

We study mathematically a method for discovering which gene is related to a cell phenotype of interest. The method is based on RNA interference -- a molecular process for gene deactivation -- and on coupling the phenotype with fluorescence…

Applications · Statistics 2019-02-20 Yair Goldberg , Yuval Nov