BIF401 HANDOUTS PDF, BIF401 Handouts pdf
BIF401: Bioinformatics I (PDF)
Bioinformatics is a multidisciplinary field that develops software and tools for understanding biological data, especially where data sets are large and complex. As a multidisciplinary science field, bioinformatics combines biology, chemistry, physics, computer science, information engineering, mathematics, and mathematics to analyze and interpret biological data.
Course Category: Bioinformatics
Bioinformatics (Background, Needs, Applications and Frontiers), Gene, mRNA and Protein, Transcription, Nucleotides, Translation, Amino Acids, Storage of Biological Sequence Information (Entrez, Uniprot), Comparing Sequences (Similarities and Differences in Sequences, Pairwise Sequence Alignment, Dot Plots, Identity vs. Similarity), Introduction to Alignment (Approaches, Why local alignments?, Aligning In-dels, Aligning Mutations in Sequences), Introduction to Dynamic Programming (Methodology, Needleman Wunsch Algorithm, Smith-Waterman Algorithm), Introduction to Scoring Alignments, PAM Matrices & BLOSSUM Matrices, Introduction to Multiple Sequences Alignment (Progressive Alignment for MSA, CLUSTAL), Introduction to BLAST (BLAST Algorithm, Types of BLAST),
Introduction to FASTA (FASTA Algorithm, Types of FASTA), Biological Databases and Portals, Molecular evolution and phylogeny, UPGMA, Phylogenetic Methods, DNA to RNA Sequences (Base Complementarity, Types of RNA and their Function, Significance of RNA Structures, RNA Folding, Energies of Folding, Calculating Energies of Folding, Types of RNA Secondary Structures, RNA Tertiary Structures, Circular Representation of RNA Structures, Experimental Methods for Determining RNA Structures, Strategies for RNA Structure Prediction, Dot Plots for RNA 2` Structure Prediction), Energy-Based Methods (Zuker Algorithm, Martinez Algorithm), Dynamic Programming Approaches, Nussinov -Jacobson Algorithm, Score Calculations and Traceback, Comparison of Algorithms, Web Resources:
RNA Bricks & MFOLD, Coding of Amino Acids, Open Reading Frames and its Extraction, Sequencing Proteins, Application of MS in sequencing, Techniques for MS Proteomics and its Types, Bottom-Up Proteomics, Top-Down Proteomics, Protein Identification, Protein Ionization Techniques, MS1 and Intact Protein Mass, Scoring Intact Protein Mass, Protein Fragmentation Techniques, Tandem MS, Measuring Experimental Fragment`s Mass, Calculating Theoretical Fragment`s Mass, Peptide Sequence Tags and its extracting, Using Peptide Sequence Tags in Protein Search, Scoring Peptide Sequence Tags, In silico Protein Fragmentation,
Protein Sequence Database Search Algorithm, Integrative Scoring Schemes, Large Scale Proteomics, Proteomics Data File Formats, RAW File Format, MGF File Format, Open MS Data, Online Proteomics Tools – Mascot & ProSight PTM, Case Studies, Properties of Amino Acids, Structural Traits of Amino Acids, Introduction to Protein Folding, Protein Structures, Primary, Secondary, Tertiary and Quaternary Structures, Introduction to Protein Bond Angles, Ramachandran Plot, Structure Visualization, Protein Data Bank, Visualization Techniques, Introduction to Energy of Protein Structures, Protein Structures – Alpha Helices, Beta Sheets, Loops, Coils, Structure Classification, Protein Domains, CATH Classification, Classification Databases, Algorithms for Structure Classification,
Protein Structure Comparison, Protein Structure Prediction, Predicting Secondary Structures, Introduction to Chou Fasman Algorithm, Introduction to Homology modelling, Fold Recognition/Threading, Online Tools for Fold Recognition, iTASSER, GOR Algorithm, 3D-1D Bowie Algorithm, Machine Learning Approaches to Structure, Neural Networks for Structured Prediction, Introduction to Neural Networks, PSIPRED, Introduction to Hidden Markov Models, Ab initio modelling, Hinds and Levitt Algorithm, Computational Assessment of Structure Prediction (CASP), Online Tools for Homology Modelling, Databases for Structure Modelling
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BIF401: Bioinformatics I Handouts
Bioinformatics is becoming a popular science for many reasons. It is a multi-level field as it integrates digital biological data which includes humans, plants, animals and microorganisms. Although it is a new field, it is growing rapidly. Requires low-cost infrastructure and is virtually free of laboratory equipment. As bioinformatics data affects different types of people, plants and micro-organisms, which gives us many opportunities for scientific discovery. BIF401 Handouts pdf
The field of Bioinformatics and Computational Biology is characterized by a very diverse combination of traditional studies. Informatics and Bio-science are umbrella terms provided by a group of integrated disciplines that make up this field, but many common areas contribute to the set of tools needed by individuals trained in this new and growing field of different disciplines. Biomedical Engineering, Electrical and Computer Engineering, Computer Science, Applied Mathematics, Genetics, Biology, Anatomy and Cell Biology, Micro Biology, and Biostatistics are major integrated disciplines.
Applications Of Bioinformatics
Bioinformatics is used in general life in many ways such as Genomics, transcriptomics, Proteomics, Metabolomics, Structural Proteomics, Designing Drugs, System Biology and customization of medicines for treatment. In addition to these applications, Bioinformatics has introduced strategies that have enabled us to generate big data about biology and its application. And step by step the use of bioinformatics has increased from the genomic level to the whole system level.