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Target discovery strategy (V-U)
- Course:Advanced Bioinformatics (V-U)
- Discipline:Basic and Health Sciences
- Institute:Virtual University
- Instructor(s): Dr. Muhammad Usman Ghani Khan
- Level:Graduate
Advanced Bioinformatics (V-U)
- Adoption studies (V-U)
- Adopton Studies (V-U)
- Alignment module (V-U)
- Advanved Bio Informatics (V-U)
- Alphabets, symbols and sequences (V-U)
- Anatomy of java prog (V-U)
- Anatomy of java program (V-U)
- Association rule (V-U)
- Application Areas (V-U)
- Association Rule Mining (V-U)
- Automated tools (V-U)
- Bayes theorem (V-U)
- Bayes’ theorem (V-U)
- Bayesian inference (V-U)
- Bioethics (V-U)
- Bioethics introduction and purposes (V-U)
- Bioinformatic Definitions (V-U)
- Biomedical annotated corpora (V-U)
- Bioinformatics toolbox (V-U)
- BioTechnogy (V-U)
- BioTechnogy Introduction (V-U)
- BLAST (V-U)
- Blast algorithm (V-U)
- Blast variants (V-U)
- Building own ontology (V-U)
- Cell Cycle Phase Markers (V-U)
- Cell cycle and cancer (V-U)
- Cell cycle phase markers cont (V-U)
- Cell cycle target identification (V-U)
- Central dogma in Biojava (V-U)
- Classification (V-U)
- Characteristics of Biological Data (V-U)
- Cloud Architecture, Cloud Delivery Models (V-U)
- Cloud computing and MSA (V-U)
- Cloud Deployment Models (V-U)
- Cloud computing introduction (V-U)
- Cloud Deployment Models cont (V-U)
- Clustering (V-U)
- Components of Semantic Web (Ontology) (V-U)
- CODIS database (V-U)
- Components of Semantic Web (V-U)
- Computer programs (V-U)
- Confusion matrix (V-U)
- Computer Vision (V-U)
- Consensus tree (V-U)
- Corpus design for biomedical annotated data (V-U)
- Cyclins and cdks (V-U)
- Creation of biomedical annotated corpora steps (V-U)
- Data integration (V-U)
- Data integration cont (V-U)
- Data Integration Techniques (V-U)
- Data Management Life Cycle (V-U)
- Data Models for Bioinformatics (V-U)
- Data Organization Cont (V-U)
- Data Organization (V-U)
- Data server (V-U)
- Data visualization (V-U)
- Databank Challenges (V-U)
- Database Search (V-U)
- Databank generation steps (V-U)
- DB Architecture (V-U)
- Decision Tree (V-U)
- Decision tree cont (V-U)
- Difference between ethical and legal issues (V-U)
- Definitions (V-U)
- Distance based methods (V-U)
- Distance matrix (V-U)
- Distance measures (V-U)
- DNA Finger Printing (V-U)
- DNA and Parts (V-U)
- DNA Profile (V-U)
- DNA Profile Methods (V-U)
- Document Classification (V-U)
- Docking and scoring (V-U)
- Dot plots (V-U)
- Drug discovery methods (V-U)
- Download server (V-U)
- Drug discovery technologies (V-U)
- Drug discovery: Pipeline (V-U)
- eHealth privacy concerns (V-U)
- eHealth security concerns contiue (V-U)
- eHealth security concerns (V-U)
- Ethic terminology (V-U)
- Ethical issues in bioinformatics (V-U)
- Evolution introduction (V-U)
- Familial aggregation (V-U)
- Existing biomedical annotated corpora. Annotation & Information Extraction. (V-U)
- FASTA (V-U)
- Features and annotations (V-U)
- Features and functions (V-U)
- Features and anutations (V-U)
- Features Extraction (V-U)
- Fitch algorihms (V-U)
- Forensic Science plus Limitations of Thumb fingerprinting (V-U)
- Genes and species tree (V-U)
- Generation of our own data bank (V-U)
- Genetic Engineering (V-U)
- Genetically Modified (GM) Crops (V-U)
- Global alignment (V-U)
- Genetically Modified Crops (V-U)
- GO ontology (V-U)
- Guidelines for Biological Data Protection (V-U)
- High performance computing components (V-U)
- HMM gene finidng (V-U)
- HIPAA – the legal basis for eHealth privacy (V-U)
- HMM introduction (V-U)
- HMM limitations and Software (V-U)
- HMM structure (V-U)
- Image Enhancement- neighborhood processing (V-U)
- Identifying lead component (V-U)
- Image Enhancement- point processing (V-U)
- Image mining (V-U)
- Information Retrieval (V-U)
- Information Extraction for Bioinformatics Documents (V-U)
- Instructor Introduction (V-U)
- Introduction – Ontology-Web Sementics (V-U)
- Introduction to Biological Concepts (V-U)
- Introduction to biojava (V-U)
- Introduction to cell cycle: key to drug discovery (V-U)
- Introduction to Drug Discovery (V-U)
- Introduction to Drug Discovery: Technology and Strategies (V-U)
- Introduction to HPC (V-U)
- Introduction to genetic epidemiology (V-U)
- Introduction to information retrieval (V-U)
- Introduction to Phylogenetics (V-U)
- Introduction to structural biology (V-U)
- Ir evaluation measures (V-U)
- Ir in bioinformatics (V-U)
- IR Models (V-U)
- Ir in biological dbs (V-U)
- IR models cont (V-U)
- Issues with MSA, Cloud Computing for MSA Problem (V-U)
- Java introduction (V-U)
- Iterative methods (V-U)
- Knowledge discovery (V-U)
- Konwledge discovery techniques (V-U)
- Likelihood (V-U)
- Machine learning (V-U)
- Local alignment (V-U)
- Markov Chain (V-U)
- Matlab basics (V-U)
- MBO (V-U)
- Matlab Introduction (V-U)
- Medical imaging (V-U)
- MedTag: a collection of biomedical annotations (V-U)
- Methods used in DNA profiling (V-U)
- Methods of DD (V-U)
- ML Concepts (V-U)
- ML Concepts cont (V-U)
- Ml other applications (V-U)
- morphological processing (V-U)
- Molecule clock (V-U)
- Motivation (V-U)
- MSA algorithms (V-U)
- MSA other methods (V-U)
- MSA for phylogenetics – stage 2 (V-U)
- Multiple Sequence Alignment – Introduction (V-U)
- Natural language Processing (V-U)
- Neighbor join (V-U)
- Need of biomedical annotated corpora (V-U)
- Networks (V-U)
- Neural Network (V-U)
- Neural networks (V-U)
- NLP steps (V-U)
- Neutral theory (V-U)
- Object recognition (V-U)
- Object-Oriented Data Modeling (V-U)
- Ontology of Autism (V-U)
- Ontology (V-U)
- Open Biomedical Ontologies (OBO) (V-U)
- Optimization of lead component (V-U)
- Pairwise Sequence Alignment – Introduction (V-U)
- Organization for ethical lookup ahima-amia-himss (V-U)
- Pharmacogenomics applications (V-U)
- Pharmacokinetics applications (V-U)
- Phases of cell cycle (V-U)
- Phylip (V-U)
- Phylogenetic Analysis Stage 3 (V-U)
- Phyloblast (V-U)
- Phylogenetic tree (V-U)
- Phylogeny Analysis (V-U)
- Phylogeny tree algorithms (V-U)
- Phylogeny tree (V-U)
- Phylogeny tree basic (V-U)
- Prediction of important regions from structure (V-U)
- Problems of NLP (V-U)
- Processing engine (V-U)
- Problems with data integration (V-U)
- Programming languages (V-U)
- Progressive msa (V-U)
- Qsar methods (V-U)
- Proteins and genes (V-U)
- Regulation of cell cycle (V-U)
- Related Concepts (V-U)
- Restoration and segmentation (V-U)
- Reporting server (V-U)
- Search Engines (V-U)
- Search Engines in Bioinformatics (V-U)
- Sequence acquisition – stage 1 (V-U)
- Search engines-2 (V-U)
- Sequence input output (V-U)
- Single Nucleotide Polymorphisms (V-U)
- Snomed and umls (V-U)
- Stages of image processing (V-U)
- Stage 2 – defintions (V-U)
- STR(short tandem repeats) (V-U)
- Strategy to identify possible drug targets (V-U)
- Target discovery strategy (V-U)
- Target validation (V-U)
- Target identification strategies (V-U)
- Tree building methods- stage 4 (V-U)
- Tree evaluation (V-U)
- Types of sequence alignment (V-U)
- Types of ontologies (V-U)
- Validation of targets (V-U)
- Virtual high –throughput in silico- screening. (V-U)
- Variable number tandum repeats (V-U)
- Virtualization (V-U)
- VNTRs (Variable number tandem repeats) (V-U)
- What We will study (V-U)
- Wordnet for synonym replacement (V-U)