Teaching & Learning

Virtual Classroom

Virtual classroom is active for M.Sc. Bioinformatics Students, University of Allahabad.

Academic-outreach activities:

Dr. Pramod Katara

Invited/Expert Lectures:

  • 'Computational approaches for drug target identification and their impact on drug designing' in SERB sponsored workshop on 'Computer Aided Drug Designing' organized by Department of Biotechnology, MNNIT-Allahabad, (10-11 September, 2022).

  • 'An Introduction to Molecular Docking Concepts' in AICTE sponsored (ATAL) FDP ON 'COMPUTER AIDED DRUG DESIGN IN DRUG DISCOVERY' organized by IIIT-Allahabad, (6-10 September, 2021).

  • 'Sequence Analysis in NGS ERA'' in Lecture Series Webinar on Theme 'Biological Sciences' organized by VBSP-University, (15 – 30 June, 2020).

  • 'Protein-Protein Interaction to protein-interactome: Network approach' in National symposium cum workshop on 'Biomolecular Recognition and Dynamics' held at Banasthali University (11-13 January, 2019).

  • 'In-silico primer designing demonstration' in Short term training course on 'Hands on technique used in biotechnology' held at the University of Allahabad (17 December, 2018 to 1 January, 2019).

  • 'RNA-seq Data analysis for transcriptome profiling' in 'Short term course on Next generation sequencing data analysis' held at MNNIT-Allahabad (17-23 December, 2018).

  • 'Stem Cell and its importance in drug designing' in Hands on workshop on ‘’stem cell biology techniques’’ at University of Allahabad (1-8 September, 2016).

  • 'Role of Transcriptomics in Crop improvement' in National workshop on 'Genomics for Crop Improvement' held at MNNIT-Allahabad (23-29 December, 2015).

  • 'Tools for microarray data analysis' in National workshop on 'In-silico Genome and Proteome analysis' held at the Centre of Bioinformatics, Banasthali University (8-10 March, 2014).

  • 'Transcriptomics: Towards gene expression profiling' in National workshop on 'Bioinformatics approaches in Genomics, Proteomics and Transcriptomics' held at NBFGR- Lucknow (16-23 November, 2013).

Session Chair:

Learning:

  • Online Short-term Course on 'Computer-Aided Drug Design and Protein Analysis'. Organized by IIT-BHU, Banaras (22-26 February , 2021).

  • Faculty Development Program on “Bioinformatics, Big Data and Drug Discovery – Prospects & Challenges”, Organized by G. B. Pant Institute of Engineering and Technology, Pauri Garhwal, Uttarakhand (14-24 September, 2020).

  • Pedagogical Training for Teachers on 'Tools for Online Teaching Learning and Evaluation'. Organized by School of Mathematical Sciences, Swami Ramanand Teerth Marathwada University, Nanded (1- 6 July, 2020).

  • National Webinar on 'Intellectual Property Rights: Protection of Intellectual property and way forward'. IPR-Cell VBSP-University, Jaunpur (22-23 May, 2020).

  • e-Faculty Development Program on 'Global Pandemic: COVID19 - Challenges and Opportunities for India'. Institute of Technology & Science, Ghaziabad (16-17 May, 2020).

  • Faculty Development Program on 'Data Sciences' by Data Analytics Lab, Indian Institute of Information Technology-Allahabad (8-12 November, 2019).

  • RTG Big Data Research Allahabad Summer School- by Allahabad University and Interdisciplinary Center of Scientific computing (IWR) of Heidelberg University (1-5 April, 2019).

  • Workshop on recent trends in 'Artificial Intelligence and Deep Learning'. by Dept. of Electronics and communication, University of Allahabad (25 February, 2019).

  • Annual BSBE Winter meeting 'Computational Biology in Disease Mechanism' by Dept. of Biological Science and Bioengineering, IIT-Kanpur (7-9 December, 2018).

miscellaneous

Glossary:

  • Guilt by association: The attribution of guilt to individuals because of the people or organizations with which they associate, rather than because of any crime that they have committed. In computational biology Guilt by association is utilized as one of the Predictive algorithm. 'Guilt by association states that genes/proteins which are homologs/associated or interacting are more likely to share function'.

  • Magic bullet: A chemical substance can selectively affect physiological processes in the body. A ‘magic bullet’ is a substance that can seek out and kill the disease causing agents only [Paul Ehrlich (1854 – 1915), Received the Nobel Prize for Physiology and Medicine 1908. He developed the term ‘magic bullet’].

  • Metaomics: High-throughput, global analysis of DNA, RNA, proteins, or metabolites isolated directly from a community of organisms living in a particular environment.

  • Omics: The term 'omics' refers to a field of systemic study in biology ending in -omics, such as genomics, transcriptomics, proteomics, metabolomics and interactomics. The related suffix -ome is used to address the objects of study of such fields, such as the genome, transcriptome, proteome metabolome and interactome respectively.

  • Placebo-controlled: A descriptive term for a clinical study in which one group of patients (the "control" group) receives an inactive substance, or placebo, while the drug being evaluated is given to another group.

  • Transcriptomics: Transcriptomics is the study of the transcriptome—the complete set of RNA transcripts that are produced by the genome, under specific circumstances or in a specific cell—using high-throughput methods, such as microarray and RNA-seq analysis. Comparison of transcriptomes allows the identification of genes that are differentially expressed in distinct cell populations, or in response to different treatments (https://www.nature.com/subjects/transcriptomics).


“Omics” Sciences: The term genome was first proposed by Hans Winkler, a professor of botany at the University of Hamburg, Germany, in 1920 (Winstead 2007). It was coined to describe the total hereditary material contained in an organism long before it was known that genetic information is encoded by DNA. Today genome is used to describe all the DNA present in a haploid set of chromosomes in eukaryotes, in a single chromosome in bacteria, or all the DNA or RNA in viruses. The suffix ome is derived from the Greek for “all” or “every.” In the past several years, many related neologistic omes have come into use to describe related fields of study that encompass other aspects of large-scale biology. Some of them are:

  • The proteome, the total set of proteins in an organism, tissue, or cell type; proteomics is the associated field of study.

  • The transcriptome, the total set of RNAs found in an organism, tissue, or cell type.

  • The metabolome, the entire complement of metabolites that are generated in an organism, tissue, or cell type.

  • The interactome, the entire set of molecular interactions in an organism.

The list of “omes” and “omics” is growing longer as scientists develop new tools and approaches for carrying out large-scale studies of biological systems.