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Antao, Tiago. Bioinformatics with Python cookbook: use modern Python libraries and applications to solve real-world computational biology problems / Tiago Antao. — Third edition. — 1 online resource : illustrations. — Includes index. — <URL:http://elib.fa.ru/ebsco/3384138.pdf>.Дата создания записи: 06.01.2023 Тематика: Python (Computer program language); Bioinformatics.; Computational biology. Коллекции: EBSCO Разрешенные действия: –
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Оглавление
- Cover
- Title Page
- Copyright and Credits
- Contributors
- Table of Contents
- Preface
- Chapter 1: Python and the Surrounding
Software Ecology
- Installing the required basic software with Anaconda
- Getting ready
- How to do it...
- There’s more...
- Installing the required software with Docker
- Getting ready
- How to do it...
- See also
- Interfacing with R via rpy2
- Getting ready
- How to do it...
- There’s more...
- See also
- Performing R magic with Jupyter
- Getting ready
- How to do it...
- There’s more...
- See also
- Installing the required basic software with Anaconda
- Chapter 2: Getting to Know NumPy, pandas, Arrow, and Matplotlib
- Using pandas to process vaccine-adverse events
- Getting ready
- How to do it...
- There’s more...
- See also
- Dealing with the pitfalls of joining pandas DataFrames
- Getting ready
- How to do it...
- There’s more...
- Reducing the memory usage of pandas DataFrames
- Getting ready
- How to do it…
- See also
- Accelerating pandas processing with
Apache Arrow
- Getting ready
- How to do it...
- There’s more...
- Understanding NumPy as the engine behind Python data science and bioinformatics
- Getting ready
- How to do it…
- See also
- Introducing Matplotlib for chart generation
- Getting ready
- How to do it...
- There’s more...
- See also
- Using pandas to process vaccine-adverse events
- Chapter 3: Next-Generation Sequencing
- Accessing GenBank and moving around NCBI databases
- Getting ready
- How to do it...
- There’s more...
- See also
- Performing basic sequence analysis
- Getting ready
- How to do it...
- There’s more...
- See also
- Working with modern sequence formats
- Getting ready
- How to do it...
- There’s more...
- See also
- Working with alignment data
- Getting ready
- How to do it...
- There’s more...
- See also
- Extracting data from VCF files
- Getting ready
- How to do it...
- There’s more...
- See also
- Studying genome accessibility and filtering SNP data
- Getting ready
- How to do it...
- There’s more...
- See also
- Processing NGS data with HTSeq
- Getting ready
- How to do it...
- There’s more...
- Accessing GenBank and moving around NCBI databases
- Chapter 4: Advanced NGS Data Processing
- Preparing a dataset for analysis
- Getting ready
- How to do it…
- Using Mendelian error information for quality control
- How to do it…
- There’s more…
- Exploring the data with standard statistics
- How to do it…
- There’s more…
- Finding genomic features from sequencing annotations
- How to do it…
- There’s more…
- Doing metagenomics with QIIME 2 Python API
- Getting ready
- How to do it...
- There’s more...
- Preparing a dataset for analysis
- Chapter 5: Working with Genomes
- Technical requirements
- Working with high-quality reference genomes
- Getting ready
- How to do it...
- There’s more...
- See also
- Dealing with low-quality genome references
- Getting ready
- How to do it...
- There’s more...
- See also
- Traversing genome annotations
- Getting ready
- How to do it...
- There’s more...
- See also
- Extracting genes from a reference using annotations
- Getting ready
- How to do it...
- There’s more...
- See also
- Finding orthologues with the Ensembl REST API
- Getting ready
- How to do it...
- There’s more...
- Retrieving gene ontology information from Ensembl
- Getting ready
- How to do it...
- There’s more...
- See also
- Chapter 6: Population Genetics
- Managing datasets with PLINK
- Getting ready
- How to do it...
- There’s more...
- See also
- Using sgkit for population genetics analysis with xarray
- Getting ready
- How to do it...
- There’s more...
- Exploring a dataset with sgkit
- Getting ready
- How to do it...
- There’s more...
- See also
- Analyzing population structure
- Getting ready
- How to do it...
- See also
- Performing a PCA
- Getting ready
- How to do it...
- There’s more...
- See also
- Investigating population structure with admixture
- Getting ready
- How to do it...
- There’s more...
- Managing datasets with PLINK
- Chapter 7: Phylogenetics
- Preparing a dataset for phylogenetic analysis
- Getting ready
- How to do it...
- There’s more...
- See also
- Aligning genetic and genomic data
- Getting ready
- How to do it...
- Comparing sequences
- Getting ready
- How to do it...
- There’s more...
- Reconstructing phylogenetic trees
- Getting ready
- How to do it...
- There’s more...
- Playing recursively with trees
- Getting ready
- How to do it...
- There’s more...
- Visualizing phylogenetic data
- Getting ready
- How to do it...
- There’s more...
- Preparing a dataset for phylogenetic analysis
- Chapter 8: Using the Protein Data Bank
- Finding a protein in multiple databases
- Getting ready
- How to do it...
- There’s more
- Introducing Bio.PDB
- Getting ready
- How to do it...
- There’s more
- Extracting more information from a PDB file
- Getting ready
- How to do it...
- Computing molecular distances on a PDB file
- Getting ready
- How to do it...
- Performing geometric operations
- Getting ready
- How to do it...
- There’s more
- Animating with PyMOL
- Getting ready
- How to do it...
- There’s more
- Parsing mmCIF files using Biopython
- Getting ready
- How to do it...
- There’s more
- Finding a protein in multiple databases
- Chapter 9: Bioinformatics Pipelines
- Introducing Galaxy servers
- Getting ready
- How to do it…
- There’s more
- Accessing Galaxy using the API
- Getting ready
- How to do it…
- Deploying a variant analysis pipeline with Snakemake
- Getting ready
- How to do it…
- There’s more
- Deploying a variant analysis pipeline with Nextflow
- Getting ready
- How to do it…
- There’s more
- Introducing Galaxy servers
- Chapter 10: Machine Learning
for Bioinformatics
- Introducing scikit-learn with a PCA example
- Getting ready
- How to do it...
- There’s more...
- Using clustering over PCA to classify samples
- Getting ready
- How to do it...
- There’s more...
- Exploring breast cancer traits using Decision Trees
- Getting ready
- How to do it...
- Predicting breast cancer outcomes using Random Forests
- Getting ready
- How to do it…
- There’s more...
- Introducing scikit-learn with a PCA example
- Chapter 11: Parallel Processing
with Dask and Zarr
- Reading genomics data with Zarr
- Getting ready
- How to do it...
- There’s more...
- See also
- Parallel processing of data using Python multiprocessing
- Getting ready
- How to do it...
- There’s more...
- See also
- Using Dask to process genomic data based on NumPy arrays
- Getting ready
- How to do it...
- There’s more...
- See also
- Scheduling tasks with dask.distributed
- Getting ready
- How to do it...
- There’s more...
- See also
- Reading genomics data with Zarr
- Chapter 12: Functional Programming
for Bioinformatics
- Understanding pure functions
- Getting ready
- How to do it...
- There’s more...
- Understanding immutability
- Getting ready
- How to do it...
- There’s more...
- Avoiding mutability as a robust development pattern
- Getting ready
- How to do it...
- There’s more...
- Using lazy programming for pipelining
- Getting ready
- How to do it...
- There’s more...
- The limits of recursion with Python
- Getting ready
- How to do it...
- There’s more...
- A showcase of Python’s functools module
- Getting ready
- How to do it...
- There’s more...
- See also...
- Understanding pure functions
- Index
- Other Books You May Enjoy
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