Tools for in-Silico Reconstruction and Visualization of Gene Regulatory Networks (GRN)

Plethora of software tools are available for inference and visualization of Gene Regulatory Networks (GRN) with their relative strengths and weaknesses. System and computational biologists quite often find it difficult to select a candidate tool for their experimentation. In this paper we present a...

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Vydáno v:2015 Second International Conference on Advances in Computing and Communication Engineering s. 421 - 426
Hlavní autoři: Kharumnuid, Graciously, Roy, Swarup
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.05.2015
Témata:
Ben
Benchmark testing
Bio-informatics
Bioinformatics Tools
Computational Biology
Data visualization
Gene expression
Gene Regulatory Networks
Inference algorithms
Java
Layout
Network Inference Algorithms
Network Predictions
Network Visualization
Reverse Engineering
Software
Synthetic Gene Expression
System Biology
ISBN:9781479917334, 1479917338
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Abstract Plethora of software tools are available for inference and visualization of Gene Regulatory Networks (GRN) with their relative strengths and weaknesses. System and computational biologists quite often find it difficult to select a candidate tool for their experimentation. In this paper we present a comprehensive study on some of the promising and influential software tools developed so far for in-silico reconstruction and visualization of GRN. We discuss the features of each tool, the underlying technology used along with their relative merits and limitations. Researchers normally use synthetic gene expression data for evaluation and validation of GRN methods. We also discuss various synthetic data generators and tools that support benchmarking against gold standards like DREAM challenge data. Finally, we suggest few important issues that may be helpful for the development of effective inference and visualization softwares.
AbstractList Plethora of software tools are available for inference and visualization of Gene Regulatory Networks (GRN) with their relative strengths and weaknesses. System and computational biologists quite often find it difficult to select a candidate tool for their experimentation. In this paper we present a comprehensive study on some of the promising and influential software tools developed so far for in-silico reconstruction and visualization of GRN. We discuss the features of each tool, the underlying technology used along with their relative merits and limitations. Researchers normally use synthetic gene expression data for evaluation and validation of GRN methods. We also discuss various synthetic data generators and tools that support benchmarking against gold standards like DREAM challenge data. Finally, we suggest few important issues that may be helpful for the development of effective inference and visualization softwares.
Author Kharumnuid, Graciously
Roy, Swarup
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  givenname: Swarup
  surname: Roy
  fullname: Roy, Swarup
  email: swarup@nehu.ac.in
  organization: Dept. of Inf. Technol., North-Eastern Hill Univ., Shillong, India
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SubjectTerms Ben
Benchmark testing
Bio-informatics
Bioinformatics Tools
Computational Biology
Data visualization
Gene expression
Gene Regulatory Networks
Inference algorithms
Java
Layout
Network Inference Algorithms
Network Predictions
Network Visualization
Reverse Engineering
Software
Synthetic Gene Expression
System Biology
Title Tools for in-Silico Reconstruction and Visualization of Gene Regulatory Networks (GRN)
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