Screen LibraryTranscriptomics and gene regulation /
This volume focuses on modern computational and statistical tools for translational gene expression and regulation research to improve prognosis, diagnostics, prediction of severity, and therapies for human diseases. It introduces some of state of the art technologies as well as computational and st...
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| Group Author: | ; |
|---|---|
| Published: |
Springer,
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| Publisher Address: | Dordrecht : |
| Publication Dates: | [2016] |
| Literature type: | Book |
| Language: | English |
| Series: |
Translational Bioinformatics,
9 |
| Subjects: | |
| Summary: |
This volume focuses on modern computational and statistical tools for translational gene expression and regulation research to improve prognosis, diagnostics, prediction of severity, and therapies for human diseases. It introduces some of state of the art technologies as well as computational and statistical tools for translational bioinformatics in the areas of gene transcription and regulation, including the tools for next generation sequencing analyses, alternative spicing, the modeling of signaling pathways, network analyses in predicting disease genes, as well as protein and gene expres |
| Carrier Form: | x, 185 pages : color illustrations, color portraits ; 25 cm. |
| Bibliography: | Includes bibliographical references. |
| ISBN: |
9789401774482 940177448X |
| Index Number: | QH450 |
| CLC: | Q756 |
| Call Number: | Q756/T772 |
| Contents: | The Analyses of Global Gene Expression and Transcription Factor Regulation -- Global Approaches to Alternative Splicing and its Regulation -- Recent Advances and Open Questions -- Long Non-coding RNAs: Critical Regulators for Cell Lineage Commitment in the Central Nervous System -- Gene expression models of signaling pathways -- From Gene Expression to Disease Phenotypes: Network-Based Approaches to Study Complex Human Diseases -- Introduction to Isoform Sequencing using Pacific Biosciences Technology (Iso-Seq) -- Systematic and Integrative Analysis of Gene Expression to Identify Feature Gen |