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{ "item_title" : "Bioinformatics with Python", "item_author" : [" Joseph Solomon "], "item_description" : "Bioinformatics with Python: Deep Learning Pipelines for Gene Expression Prediction is a hands-on guide that bridges molecular biology and data science through real Python code.From raw sequencing reads to deep learning-based gene expression models, this book teaches you how to design, automate, and interpret complete bioinformatics workflows.Inside, you'll learn how to: Preprocess and visualize genomic and transcriptomic datasetsBuild and train deep learning models to predict gene activityParse and analyze FASTQ, BAM, and VCF files using PythonApply reproducible workflows with Snakemake and BiopythonIntegrate public datasets and annotate variants programmaticallyVisualize biological insights with matplotlib and seabornEach chapter includes step-by-step scripts, real-world examples, and executable workflows built entirely in Python.Whether you're a biologist learning to code or a data scientist entering genomics, this book gives you the essential toolkit to move from raw data to biological discovery - confidently and reproducibly.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/826/893/9798268931679_b.jpg", "price_data" : { "retail_price" : "19.00", "online_price" : "19.00", "our_price" : "19.00", "club_price" : "19.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Bioinformatics with Python|Joseph Solomon

Bioinformatics with Python : Deep Learning Pipelines for Gene Expression Prediction using Python

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Overview

Bioinformatics with Python: Deep Learning Pipelines for Gene Expression Prediction is a hands-on guide that bridges molecular biology and data science through real Python code.
From raw sequencing reads to deep learning-based gene expression models, this book teaches you how to design, automate, and interpret complete bioinformatics workflows.
Inside, you'll learn how to:

  • Preprocess and visualize genomic and transcriptomic datasets
  • Build and train deep learning models to predict gene activity
  • Parse and analyze FASTQ, BAM, and VCF files using Python
  • Apply reproducible workflows with Snakemake and Biopython
  • Integrate public datasets and annotate variants programmatically
  • Visualize biological insights with matplotlib and seaborn
Each chapter includes step-by-step scripts, real-world examples, and executable workflows built entirely in Python.
Whether you're a biologist learning to code or a data scientist entering genomics, this book gives you the essential toolkit to move from raw data to biological discovery - confidently and reproducibly.

This item is Non-Returnable

Details

  • ISBN-13: 9798268931679
  • ISBN-10: 9798268931679
  • Publisher: Independently Published
  • Publish Date: October 2025
  • Dimensions: 9 x 6 x 0.64 inches
  • Shipping Weight: 0.91 pounds
  • Page Count: 306

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