
Advances in Bioinformatics and Computational Biology
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
The 10 revised full papers and 5 short papers were carefully reviewed and selected from 28 submissions. The papers address a broad range of current topics in computational biology and bioinformatics.
More details
Other editions
Additional editions

Content
- Intro
- Preface
- Organization
- Contents
- Applied Bioinformatics and Computational Biology
- Comparative Transcriptome Profiling of Maytenus ilicifolia Root and Leaf
- 1 Introduction
- 2 Methods
- 2.1 Plant Material and Total RNA Isolation
- 2.2 Library Preparation and Sequencing
- 2.3 Quality Control and de novo Assembly
- 2.4 Functional Annotation
- 2.5 Differential Expression Analysis
- 2.6 Gene Ontology Enrichment and KEGG Analysis
- 3 Results and Discussion
- 3.1 De novo Assembly and Functional Annotation of M. ilicifolia
- 3.2 Identification of Differentially Expressed Transcripts in Both Tissues
- References
- Hypusine Plays a Role in the Translation of Short mRNAs and Mediates the Polyamine and Autophagy Pathways in Saccharomyces Cerevisiae
- 1 Introduction
- 2 Materials and Methods
- 2.1 RNA-seq Data Analysis
- 2.2 Strain and Growth Conditions
- 2.3 RNA Isolation and qRT-PCR
- 2.4 Protein Extraction and Western Blot Analysis
- 3 Results and Discussion
- 3.1 Translation of Short ORFs is Impaired in dys1-1 Mutant
- 3.2 Hypusination Modulates Autophagy
- References
- Topological Characterization of Cancer Driver Genes Using Reactome Super Pathways Networks
- 1 Introduction
- 2 Method
- 2.1 Reactome Functional Iteration
- 2.2 Super Pathways as Reactome FI Sub-networks
- 2.3 Super Pathways Sub-networks Enriched with Drivers Information
- 3 Results
- 3.1 Centrality Measures
- 3.2 Network Attack
- 4 Discussion and Conclusion
- References
- Bioinformatics and Computational Biology
- CellHeap: A Workflow for Optimizing COVID-19 Single-Cell RNA-Seq Data Processing in the Santos Dumont Supercomputer
- 1 Introduction
- 2 Description of the CellHeap Workflow
- 3 Results
- 3.1 Input Data and Experiment Setup
- 3.2 Environmental Setup
- 3.3 Results Discussion
- 4 Conclusion
- References
- Combining Orthology and Xenology Data in a Common Phylogenetic Tree
- 1 Introduction
- 2 Preliminaries
- 3 Tree-Like Pairs of Maps
- 4 Tree-Like Pairs of Maps with Constraints
- 5 Concluding Remark
- References
- ContFree-NGS: Removing Reads from Contaminating Organisms in Next Generation Sequencing Data
- 1 Introduction
- 2 Implementation
- 3 Evaluation
- 4 Conclusion
- References
- Deep Learning-Based COVID-19 Diagnostics of Low-Quality CT Images
- 1 Introduction
- 2 Dataset
- 3 Methodology
- 3.1 Data Preprocessing
- 3.2 Deep Neural Network Architectures
- 4 Experimental Evaluation
- 4.1 Data Preprocessing
- 4.2 Transfer Learning with ResNet50
- 4.3 Image- and Exam-Level Classification of the Test Set
- 4.4 Interpreting Model Decisions
- 5 Conclusion
- References
- Feature Importance Analysis of Non-coding DNA/RNA Sequences Based on Machine Learning Approaches
- 1 Background
- 2 Pipeline for Machine Learning Classification Task
- 2.1 Prediction of sRNAs
- 2.2 Prediction of CircRNA
- 3 Results and Discussion
- 3.1 Case Study 1: sRNAs in Bacteria
- 3.2 Case Study 2: CircRNA in Humans
- 4 Conclusion
- References
- Heuristics for Cycle Packing of Adjacency Graphs for Genomes with Repeated Genes
- 1 Introduction
- 2 Definitions
- 3 Random Packings
- 4 Genetic Algorithm
- 5 Experimental Results
- 5.1 Applications with the Reversal Distance
- 5.2 Experiments with Real Biological Data
- 6 Conclusion
- References
- PIMBA: A PIpeline for MetaBarcoding Analysis
- 1 Introduction
- 2 Implementation
- 2.1 Preprocessing
- 2.2 Taxonomy Assignment
- 2.3 Plotting
- 3 Results and Discussion
- 3.1 16S rRNA Mock Community
- 3.2 Fungal ITS Mock Community
- 3.3 Metazoan COI Mock Community
- 4 Conclusion
- References
- Short Papers
- CEvADA: Co-Evolution Analysis Data Archive
- 1 Introduction
- 2 Technical Notes
- References
- FluxPRT: An Adaptable and Extensible Proteomics LIMS
- 1 Introduction
- 2 Proteomics Lab Operations
- 3 Methodology
- 3.1 Proteomics Workflow Construction and the Flux LIMS
- 3.2 Proteomics Guide
- 4 Results and Discussion
- 4.1 FluxPRT Workflow
- 4.2 Proteomics Guide
- 4.3 FluxPRT Interface
- 5 Concluding Remarks
- 6 Availability
- References
- MathPIP: Classification of Proinflammatory Peptides Using Mathematical Descriptors
- 1 Background
- 2 Materials and Methods
- 2.1 Data Selection
- 2.2 Feature Engineering
- 2.3 Experimental Setting
- 3 Results and Discussion
- 4 Conclusion
- References
- Metagenomic Insights of the Microbial Community from a Polluted River in Brazil 2020
- 1 Introduction
- 2 Materials and Methods
- 3 Results
- 4 Conclusion
- References
- Mesoscopic Evaluation of DNA Mismatches in PCR Primer-Target Hybridisation to Detect SARS-CoV-2 Variants of Concern
- 1 Introduction
- 2 Materials and Methods
- 3 Results and Discussion
- 4 Conclusion
- References
- Author Index
System requirements
File format: PDF
Copy protection: Watermark-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Use the free software Adobe Reader, Adobe Digital Editions, or any other PDF viewer of your choice (see eBook Help).
- Tablet/Smartphone (Android; iOS): Install the free app Adobe Digital Editions or another reading app for eBooks, e.g., PocketBook (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (only limited: Kindle).
The file format PDF always displays a book page identically on any hardware. This makes PDF suitable for complex layouts such as those used in textbooks and reference books (images, tables, columns, footnotes). Unfortunately, on the small screens of e-readers or smartphones, PDFs are rather annoying, requiring too much scrolling.
This eBook uses Watermark-DRM, a „soft” copy protection. This means that there are no technical restrictions to prevent illegal distribution. However, there is a personalised watermark embedded in the eBook that can be used to identify the purchaser of the eBook in the event of misuse and to provide evidence for legal purposes.
For more information, see our eBook Help page.