NDLI: Connectionist Modelling of Dynamics of Gene Expression and Reverse Engineering Gene Regulatory Networks

Content Provider	IEEE Xplore Digital Library
Author	De, R.K. Biswas, K.
Copyright Year	2006
Description	Author affiliation: Indian Stat. Inst., Kolkata (De, R.K.)
Abstract	In this article we develop two connectionist models describing the dynamics of gene expression incorporating protein concentration. The models are based on the theoretical study of Goutsias and Kim. We calculate the concentration of mRNAs and proteins at different time steps, and the concentrations of mRNAs and proteins are calculated as a function of step n. Here we consider concentration of mRNA in a cell at step n as depending on the concentration of mRNA and proteins at step (n - 1) in that particular cell. Similarly the protein concentration in a cell at step n depends on the concentration of protein and mRNA at step (n - 1) in that particular cell. Here we develop two neural network models, and estimate the parameters using neural network model through learning. Finally, gene regulatory networks are determined as network parameters. The performance of the models have effectively been tested on a real life fruit fly time series gene expression data containing various stages of development of fruit fly.
Starting Page	3813
Ending Page	3819
File Size	249166
Page Count	7
File Format	PDF
ISBN	0780394909
DOI	10.1109/IJCNN.2006.246875
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-16
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gene expression Reverse engineering Genetics Neural networks Computer networks Kinetic theory Differential equations Protein engineering Genomics Bioinformatics
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A method for modelling genetic regulatory networks by using evolving connectionist systems and microarray gene expression data

On modeling gene regulatory networks using Markov random fields

A Systematic Approach for Identifying Regulatory Interactions in Large Temporal Gene Expression Datasets from Peripheral Blood

A Systematic Approach for Identifying Regulatory Interactions in Large Temporal Gene Expression Datasets from Peripheral Blood

Bayesian Robustness in the Control of Gene Regulatory Networks

Inference of genetic networks using neural network models

Modelling genetic regulatory networks

Inference of S-system models of genetic networks using a genetic local search

A neural networks algorithm for inferring drug gene regulatory networks from microarray time-series with missing transcription factors information

Connectionist Modelling of Dynamics of Gene Expression and Reverse Engineering Gene Regulatory Networks

Similar Documents

A method for modelling genetic regulatory networks by using evolving connectionist systems and microarray gene expression data

On modeling gene regulatory networks using Markov random fields

A Systematic Approach for Identifying Regulatory Interactions in Large Temporal Gene Expression Datasets from Peripheral Blood

A Systematic Approach for Identifying Regulatory Interactions in Large Temporal Gene Expression Datasets from Peripheral Blood

Bayesian Robustness in the Control of Gene Regulatory Networks

Inference of genetic networks using neural network models

Modelling genetic regulatory networks

Inference of S-system models of genetic networks using a genetic local search

A neural networks algorithm for inferring drug gene regulatory networks from microarray time-series with missing transcription factors information

Connectionist Modelling of Dynamics of Gene Expression and Reverse Engineering Gene Regulatory Networks