Course Info
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Course Category
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Bioinformatics
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Course Level
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Graduate
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Credit Hours
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3
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Pre-requisites
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N/A
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Instructor
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Dr. Muhammad Usman Ghani Khan
Ph.D.
The University of Sheeld, UK,
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Course Contents
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Definitions, Instructor Introduction, Motivation, Related Concepts, Introduction to Biological Concepts, What We will study, Data Management Life Cycle, Data Organization, DB Architecture, Proteins and genes, Data Modeling, Data Models for Bioinformatics, Object Oriented Data Modelling, Networks, Search Engines, Data visualization, Computer Vision, Stages of image processing, Image Enhancement- neighborhood processing, Image Enhancement- point processing, Restoration and segmentation, Morphological processing, Object recognition, Medical imaging, Pairwise Sequence Alignment - Introduction, Distance measures, Types of sequence alignment, Dot plots, Global alignment, Local alignment, Database Search, FASTA, BLAST, Blast algorithm, Blast variants, Multiple Sequence Alignment - Introduction, MSA algorithms, Progressive MSA, MSA other methods, Iterative methods, Evolution introduction, Introduction to Phylogenetics, Phylogeny tree, Phylogeny tree basic, Phylogeny tree algorithms, Distance based methods, Neighbor join, Likelihood, Phylogeny Analysis, Molecule clock, Neutral theory, Genes and species tree, Sequence acquisition - stage 1, MSA for phylogenetics - stage 2, Stage 2 - definitions, Phylogenetic Analysis Stage 3, Tree building methods- stage 4, Bayesian inference, Automated tools, Phyloblast, Phylip, Tree evaluation, Fitch algorithms, Consensus tree, Distance matrix, Introduction - Ontology-Web Semantics, Components of Semantic Web, Components of Semantic Web (Ontology), Ontology, Components of SW, Open Biomedical Ontologies (OBO), GO ontology, Building own ontology, Cell Signaling Ontology, Types of ontologies, MBO (Ontology for Molecular Biology), Ontology of Autism, Bio Query Language, Snomed and UMLS, Databank for Biological Data, Data Integration Techniques, Databank Challenges, Databank generation steps, Generation of our own data bank, Download server, Processing engine, Data server, Reporting server, Application Areas, Biotechnology Introduction, Genetically Modified Crops, Genetic Engineering, Information Extraction for Bioinformatics Documents, Natural Language Processing, NLP steps, Problems of NLP, WordNet for synonym replacement, Features Extraction, Document Classification, HMM introduction, Markov Chain, HMM structure, HMM gene finding, HMM limitations and software, DNA and Parts, CODIS database, Forensic Science plus Limitations of Thumb fingerprinting, Advantages of Bioinformatics in Forensic (DNA Finger Printing - DNA Profiling), DNA Finger Printing, DNA Profile, Methods used in DNA profiling, STR (short tandem repeats), VNTRs (Variable number tandem repeats), Introduction to Drug Discovery, Drug Discovery Applications, Pharmacogenomics applications, Pharmacokinetics applications, Single Nucleotide Polymorphisms, Drug discovery methods, Drug discovery: Pipeline, Biomedical annotated corpora, Creation of biomedical annotated corpora steps, MedTag: a collection of biomedical annotations, Classification, Corpus design for biomedical annotated data, Need of biomedical annotated corpora, Introduction to Drug Discovery: Technology and Strategies, Drug discovery technologies, Existing biomedical annotated corpora, Annotation & Information Extraction, Target discovery strategy, Strategy to identify possible drug targets, Target validation, Identifying lead component, Optimization of lead component, Mechanism of Drug Action, Image mining, Introduction to HPC, High-performance computing components, Cloud computing introduction, Cloud Architecture, Cloud Delivery Models, Cloud Deployment Models, Virtualization, Issues with MSA, Cloud Computing for MSA Problem, Biological Data Protection, eHealth privacy concerns, HIPAA – the legal basis for eHealth privacy, eHealth security concerns, Guidelines for Biological Data Protection, Adoption studies, Introduction to cell cycle: key to drug discovery, Phases of cell cycle, Cell cycle phase markers, Regulation of cell cycle, Cyclins and CDKs, Cell cycle and cancer, Cell cycle target identification, Security Actions for Biological Data, Law and Biological Databases, Introduction to genetic epidemiology, Familial aggregation, Introduction to structural biology, Target identification strategies, Prediction of important regions from structure, Validation of targets, Virtual high-throughput in silico screening, Docking and scoring, Introduction to information retrieval, IR models, QSAR methods, IR evaluation measures, IR in biological DBs, IR in bioinformatics, Search engines-2, Search Engines in Bioinformatics, Confusion Matrix, Existing Hospital Records, Electronic Health Record, Knowledge discovery, Knowledge discovery techniques, Bayes’ theorem, Decision tree, Neural networks, Association rule, Clustering, Machine learning, ML Concepts, ML other applications, Computer programs, Programming languages, Java introduction, Anatomy of Java program, Introduction to BioJava, Alphabets, symbols, and sequences, Central dogma in BioJava, Sequence input output, Features and annotations, Protein Structure, Data integration, Alignment module, Python basics, BioPython Basics, Introduction to BioPython, Sequence object, Phylogenetic tree IO, Protein Structure using BioPython, Utils Entrez, Matlab Introduction, Matlab basics, Bioinformatics toolbox, Features and functions, Bioinformatics tasks, Phylogenetic analysis, Protein Property Analysis, Data Integration -2, Problems with data integration, Ethic terminology, Ethical issues in bioinformatics, Difference between ethical and legal issues, Bioethics introduction and purposes, Organization for ethical lookup AHIMA-AMIA-HIMSS
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