Titlebook: Reverse Engineering of Regulatory Networks; Sudip Mandal Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive licens

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Inference of Dynamic Growth Regulatory Network in Cancer Using High-Throughput Transcriptomic Data,ction of a correlation-based co-expression network to further downstream analysis. We have also outlined the steps for the inclusion of publicly available interaction/regulation information into the dGRN followed by relevant topological inferences. This tutorial has been designed in a way that early

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New Insights into Clinical Management for Sickle Cell Disease: Uncovering the Significant Pathways ith age. In our study, we focused on the specific pathways which are affected by the involvement of effected genes. Firstly, we retrieved the gene datasets from the publically available data source website DisGNET. Using literature-based genes, we identified 290 highly regulated genes that are direc

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A Review of Computational Approach for S-system-based Modeling of Gene Regulatory Network,vo, etc., with less computational complexity is still an open research problem to all. This paper may help the beginners or researchers who want to continue their research in the field of computational biology and bioinformatics.

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Big Data in Bioinformatics and Computational Biology: Basic Insights,d file formats. Solutions to these problems are tried to present in this chapter. In order to store massive amounts of data and provide a reasonable period for completing search queries, new database management systems other than relational ones will be necessary. Emerging advance programing approac

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Prediction and Analysis of Transcription Factor Binding Sites: Practical Examples and Case Studies development. Additionally, an example is presented on how to investigate TFBSs in the upstream regions of a group of genes, using a case study of differentially expressed genes in response to human parainfluenza virus type 1 (HPIV1) infection and interferon-beta. Key regulators identified in this c

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Next-Generation Sequencing to Study the DNA Interaction,searching DNA interactions that has completely transformed the area of genomics. NGS has also played an important part in personalized medicine, enabling the discovery of disease-causing mutations and the creation of targeted medicines. Finally, NGS has transformed the field of genomics, resulting i

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