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Bioinformatics by Nakaya Helder
This page covers the following topics related to Bioinformatics : Text Mining Gene Selection to Understand Pathological Phenotype Using Biological Big Data, Single-Cell RNA Sequencing Procedures and Data Analysis, Computational Methods for Detecting Large-Scale Structural Rearrangements in Chromosomes, Machine Learning Approaches for Biomarker Discovery Using Gene Expression Data, Bayesian Inference of Gene Expression, Comprehensive Evaluation of Error-Correction Methodologies for Genome Sequencing Data, Plant Transcriptome Assembly: Review and Benchmarking,WeMine Aligned Pattern Clustering System for Biosequence Pattern Analysis, Rational Design of Profile Hidden Markov Models for Viral Classification and Discovery, Pattern Discovery and Disentanglement for Aligned Pattern Cluster Analysis and Protein Binding Complexes Detection.
Author(s): Nakaya Helder I., PhD.
NA Pages
Bioinformatics Introduction by Mark Gerstein
This note covers the following topics: Molecular Biology, Molecular Biology Information - DNA, Protein Sequence, Macromolecular Structure and Protein Structure Details, Gene Expression Datasets, New Paradigm for Scientific Computing, General Types of Informatics in Bioinformatics, Genome Sequence, Protein Sequence, Major Application: Designing Drugs, Finding Homologues, Genome Characterization.
Author(s): Mark Gerstein
NA Pages
Bioanalytical Techniques and Bioinformatics
This note explains the following topics: Modern approaches in Bioanalysis and Bioassays, Spectroscopic techniques: UV-Visible spectroscopy, Fluorescence spectroscopy, IR spectroscopy, CD spectroscopy, and Mass spectroscopy, Light Microscopy; Fluorescence microscopy, Atomic force microscope, Electron microscope, Scanning electron microscopy, Transmission Electron microsope, Application of microscope in analyzing biological samples.
Author(s): NPTEL
NA Pages
This book is intended to serve both as a textbook for short bioinformatics courses and as a base for a self teaching endeavor. It is divided in two parts: A. Bioinformatics Techniques and B. Case Studies. Each chapter of the first part addresses a specific problem in bioinformatics and consists of a theoretical part and of a detailed tutorial with practical applications of that theory using software freely available on the Internet.
Author(s): Chanchal Kumar
197 Pages
Bioinformatics Sequence Analysis and Phylogenetics Lecture Notes (PDF 190P)
This book covers the following topics: biological basics needed in bioinformatics, Pairwise Alignment, Multiple Alignment, Phylogenetics, DNA, RNA, Transcription, Introns, Exons, and Splicing, Amino Acids.
Author(s): Sepp Hochreiter
180 Pages
Bioinformatics II Theoretical Bioinformatics and Machine Learning (PDF 394)
This book covers the following topics: Machine Learning in Bioinformatics, Theoretical Background of Machine Learning, Support Vector Machines, Error Minimization and Model Selection, Neural Networks, Bayes Techniques, Feature Selection, Hidden Markov Models.
Author(s): Sepp Hochreiter
400 Pages
Introducing Bioinformatics Concepts in CS1
This note explains the basic bioinformatics concepts via a closed lab exercise and a programming project. Also discusses the implementation of these activities and some of the results/lessons we learned.
Author(s): Erica Eddy
9 Pages
Currently this section contains no detailed description for the page, will update this page soon.
Author(s): NA
NA Pages
Currently this section contains no detailed description for the page, will update this page soon.
Author(s): NA
NA Pages
Currently this section contains no detailed description for the page, will update this page soon.
Author(s): NA
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