Biological Data Management detailed Syllabus for Biotechnology Engineering (BIOTECH), 2018 scheme has been taken from the VTUs official website and presented for the VTU students. For Course Code, Subject Names, Teaching Department, Paper Setting Board, Theory Lectures, Tutorial, Practical/Drawing, Duration in Hours, CIE Marks, Total Marks, Credits and other information, visit full semester subjects post given below. The Syllabus PDF files can also be downloaded from the official website of the university.
For all the other VTU BIOTECH 7th Sem Syllabus for BE 2018 Scheme, visit Biotechnology Engineering 7th Sem 2018 Scheme.
For all the (Open Elective-B) subjects refer to Open Elective-B Scheme. The detail syllabus for biological data management is as follows.
Course Objectives:
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Module 1
INTRODUCTION AND DATABASES: Databases Overview: PubMed, GenBank, EMBL, DDBJ, SwissProt, Uniprot, TrEMBL, PDB, EST, SCOP, Pfam, SMART; Interaction Databases, (BIND, STRING), Pathway Databases, (KEGG), Signal Transduction database (STKE), Organism Specific database (Yeast, OMIM, HGNC, Flybase, wormbase), Genome databases (GOLD), Pathogen database (PATRIC), About the January Issue of Nucleic Acids Research journal and the catalog of biological databases. Data Models: Relational, Object Oriented. Hierarchical, Semi-structured, Unstructured (e.g. Text), Model of Querying: SQL, Information Integration, Data Mining for various applications.
Module 2
MICROARRAY: Why areMicroArray Important? What is a DNA MicroArray?, Designing a MicroArray Experiment-The Basic steps, Types of MicroArray. NCBI and MicroArray Data Management, GEO (Gene Expression Omnibus), MAML, The benefits of GEO and MAML, The Promise of MicroArray Technology in Treating Disease.MicroArray Data Preprocessing, Data normalization, Measuring Dissimilarity of Expression Pattern-Distance Motifs and Dissimilarity measures, Visualizing MicroArray Data. Principal Component Analysis,MicroArray Data. NCBI and MicroArray Data Management, GEO (Gene Expression Omnibus), MAML, The benefits of GEO and MAML, The Promise of MicroArray Technology in Treating Diseases. Data Mining for specific applications.
Module 3
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Module 4
OMICS DATA MANAGEMENT: Qualitative and Quantitative Proteomics. Bioinformatics for Mass spectrometry and 2D gels. Concepts of Metabolomics, Transcriptomics and Interactomics. Computational Analysis Workflows for Protein Array Data Interpretation. Integration, Warehousing, and Analysis Strategies of Data. Integration. Data for signaling pathways, interactome reconstruction and functional analysis. Network Inference from Time Dependent data. Omics-Bioinformatics in the context of diseases, Omics-Based Identification of Pathophysiological Processes. Data Mining Methods in Omics-Based Biomarker Discovery.
Module 5
CLINICAL DATA ANALYTICS: Overview of Clinical Data Management plan, CRF design consideration, Data cleaning issues and Data processing issues, Database design consideration: Making design decisions, Operating procedures for database design, Dealing with problem data, modifying data, Quality control through database audits, Identifying and managing discrepancies, Quality control and assurance, Managing laboratory data, Storing lab data, Creating report and transferring data, Clinical data management systems, Electronic data capture systems, System Validation, Migrating, data integration and archiving data.Data Normalization and Querying Techniques. Data Mining for desired applications.
Course Outcomes:
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Question paper pattern:
- The question paper will have ten full questions carrying equal marks.
- Each full question will be for 20 marks.
- There will be two full questions (with a maximum of four sub- questions) from each module.
- Each full question will have sub- question covering all the topics under a module.
- The students will have to answer five full questions, selecting one full question from each module.
Text Books:
- Bioinformatics Database Systems Byron et al., CRC Press 2017
- Data Mining in Bioinformatics Wang et al. (eds. Springer 2005
- Computational Biology and Genome Informatics Wang et al. (eds. World Scientific, 2003
- Pattern Discovery in Biomolecular Data: Tools, Techniques and Applications Wang et al. (eds. Oxford University Press 1999
- Microarray Technology and Its Applications Uwe R. Muller, Dan V. Nicolau Springer 2005
Reference Books:
For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
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For the detail Syllabus of all other subjects of BE (BIOTECH) 7th Sem, visit Biotechnology Engineering 7th Sem Subjects.
For all (CBSE & Non-CBSC) BE/B.Tech results, visit VTU BE/B.Tech all semester results.