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BIF731 : Advanced Bioinformatics

Course Overview

Course Synopsis

In this course students will be familiar with the importance and role of Bioinformatics in following Areas; Forensic sciences, Drug discovery, Biotechnology, Genetic Engineering, Phylogenetic analysis, Medical imaging also students will be able to perform extraction and retrieval of Biological data and students will have better Understanding of annotation, integration, knowledge discovery and semantic web of biological data. More ever students will able to learn Combination of Bioinformatics with other domains such as statistics, mathematics, cloud computing and database management systems.

Course Learning Outcomes

At the end of the course, students will have good understanding of following Areas

  • Phylogeny and Phylogeny Algorithms
  • Microarray Data Analysis
  • Markov Hidden Models and their usability in bioinformatics
  • Human Disease
  • Drug Discovery: Technology and Strategies
  • Computer-aided Drug Design
  • Real life Applications of Bioinformatics
  • Role of bioinformatics in forensic
  • Role of bioinformatics and genetic engineering in agriculture
  • Medical Imaging
  • Computational Model of Human Brain
  • Dealing with large scale Biological Data
  • Informatics and Statistics in Biopharmaceutical Research
  • Database Management system for Biological Data
  • Generation of Databank For Biological Data
  • Development of Search Engine for Biological Data
  • Semantic interpretation of biological data

Course Calendar

1 Definitions
2 Instructor Introduction
3 Motivation
4 Related Concepts
5 Introduction to Biological Concepts
6 What We will study
7 Data Management Life Cycle
8 Data Organization
9 DB Architecture
10 Proteins and genes
11 Data Modeling
12 Data Models for Bioinformatics
13 Object Oriented Data Modelling
14 Networks
15 Search Engines
16 Data visualization
17 Computer Vision
18 Stages of image processing
19 Image Enhancement- neighborhood processing
20 Image Enhancement- point processing
21 Restoration and segmentation
22 morphological processing
23 Object recognition
24 Medical imaging
25 Pairwise Sequence Alignment - Introduction
26 Distance measures
27 Types of sequence alignment
28 Dot plots
29 Global alignment
30 Local alignment
31 Database Search
33 FASTA
34 BLAST
35 Blast algorithm
36 Blast variants
37 Multiple Sequence Alignment - Introduction
38 MSA algorithms
39 Progressive msa
40 MSA other methods
41 Iterative methods
42 Evolution introduction
43 Introduction to Phylogenetics
44 Phylogeny tree
45 Phylogeny tree basic
46 Phylogeny tree algorithms
47 Distance based methods
48 Neighbor join
49 Likelihood
50 Phylogeny Analysis
51 Molecule clock
52 Neutral theory
53 Genes and species tree
54 Sequence acquisition - stage 1
55 MSA for phylogenetics - stage 2
56 Stage 2 - defintions
57 Phylogenetic Analysis Stage 3
58 Tree building methods- stage 4
59 Bayesian inference
60 Automated tools
61 Phyloblast
62 Phylip
63 Tree evaluation
64 Fitch algorihms
66 Consensus tree
65 Distance matrix
67 Introduction - Ontology-Web Sementics
68 Components of Semantic Web
69 Components of Semantic Web (Ontology)
70 Ontology
237 Components of SW
71 Open Biomedical Ontologies (OBO)
72 GO ontology
73 Building own ontology
75 Types of ontologies
230 Cell Signaling Ontology
238 MBO (Ontology for Molecular Biology)
231 Ontology of Austism
232 Bio Query Language
74 Snomed and umls
233 Databank for Biological Data
79 Data Integration Techniques
80 Databank Challenges
81 Databank generation steps
82 Generation of our own data bank
83 Download server
84 Processing engine
86 Data server
85 Reporting server
88 Application Areas
87 BioTechnogy Introduction
89 Genetically Modified Crops
90 Genetic Engineering
93 Information Extraction for Bioinformatics Documents
94 Natural language Processing
95 NLP steps
96 Problems of NLP
98 Wordnet for synonym replacement
97 Features Extraction
99 Document Classification
101 HMM introduction
102 Markov Chain
103 HMM structure
104 HMM gene finidng
105 HMM limitations and Software
100 CODIS database
106 DNA and Parts
107 Forensic Science plus Limitations of Thumb fingerprinting
239 Advantages of Bio Informatics in Forensic (DNA Finger Printing - DNA Profiling)
240 DNA Finger Printing
110 DNA Profile
109 Methods used in DNA profiling
155 STR(short tandem repeats)
154 VNTRs (Variable number tandem repeats)
112 Introduction to Drug Discovery
241 Drug Discovery Applications
115 Pharmacogenomics applications
114 Pharmacokinetics applications
116 Single Nucleotide Polymorphisms
118 Drug discovery methods
117 Drug discovery: Pipeline
121 Biomedical annotated corpora?
127 Creation of biomedical annotated corpora steps
125 MedTag: a collection of biomedical annotations
124 Classification
123 Corpus design for biomedical annotated data
122 Need of biomedical annotated corpora
128 Introduction to Drug Discovery: Technology and Strategies
129 Drug discovery technologies
126 Existing biomedical annotated corpora. Annotation & Information Extraction.
130 Target discovery strategy
131 Strategy to identify possible drug targets
132 Target validation
133 Identifying lead component
134 Optimization of lead component
242 Mechanism of Drug Action
120 Image mining
135 Introduction to HPC
136 High performance computing components
137 Cloud computing introduction
138 Cloud Architecture, Cloud Delivery Models
139 Cloud Deployment Models
140 Virtualization
142 Issues with MSA, Cloud Computing for MSA Problem
243 Biological Data Protection
144 eHealth privacy concerns
145 HIPAA – the legal basis for eHealth privacy
146 eHealth security concerns
148 Guidelines for Biological Data Protection
153 Adoption studies
156 Introduction to cell cycle: key to drug discovery
157 Phases of cell cycle
158 Cell cycle phase markers
159 Regulation of cell cycle
161 Cyclins and cdks
160 Cell cycle and cancer
162 Cell cycle target identification
244 Security Actions for Biological Data
245 Law and Biological Databases
150 Introduction to genetic epidemiology
151 Familial aggregation
163 Introduction to structural biology
164 Target identification strategies
165 Prediction of important regions from structure
166 Validation of targets
169 Virtual high –throughput in silico- screening.
170 Docking and scoring
172 Introduction to information retrieval
173 Ir models
171 Qsar methods
174 Ir evaluation measures
176 Ir in biological dbs
177 Ir in bioinformatics
178 Search engines-2
179 Search Engines in Bioinformatics
234 Confusion Matrix
246 Existing Hospital Records
247 Electronic Health Record
184 Knowledge discovery
185 Konwledge discovery techniques
187 Bayes’ theorem
188 Decision tree
189 Neural networks
190 Association rule
192 Clustering
193 Machine learning
194 Ml Concepts
195 Ml other applications
205 Computer programs
206 Programming languages
207 Java introduction
208 Anatomy of java program
209 Introduction to biojava
210 Alphabets, symbols and sequences
211 Central dogma in Biojava
212 Sequence input output
213 Features and annotations
197 Data integration
248 Protein Structure
215 Alignment module
225 Python basics
249 BioPython Basics
227 Introduction to biopython
228 Sequence object
229 Phylogenetic tree io
250 Protein Structure using BioPython
251 Utils Entrez
216 Matlab Introduction
217 Matlab basics
218 Bioinformatics toolbox
220 Features and functions
221 Bioinfarmatics tasks
222 Phylogentic analysis
252 Protein Property Analysis
253 Data Integration -2
198 Problems with data integration
199 Ethic terminology
200 Ethical issues in bioinformatics
201 Difference between ethical and legal issues
202 Bioethics introduction and purposes
203 Organization for ethical lookup ahima-amia-himss
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