IISER-Mohali is an education cum research institute and we are involved in full-fledged science teaching to the under-grads, post-grads and PhD students. I teach following courses:
BIO411 - Bioinfomatics lab
Sequence composition analysis, ab intio gene prediction, Motif finding algorithms, Primer designing algorithm, Codon optimization, Sequence alignment algorithms, Phylogenetic analysis, Protein structure analysis, Molecular modelling and dynamics
IDC407 - Network Science
History of network models, Mathematics of networks, Local and global network attributes, Paths, Percolation, Price's model, Network dynamics, Network models of epidemic, Controllability
BIO459 - Epigenetics
Trans-generational epigenetic inheritance, Molecular mechanisms and evolution of epigenetic modifications, Linear and 3D genome organization, Epigenetic reprogramming during development and diseases, Genome technologies
IDC306 - Biocomputing
Practical computing for biologists using PERL/Python and R
IDC409 - Introduction to Data Science
ScienceIntroduction to big data, data storage, Hadoop, mySQL, HiveQl, missing value imputation, data scaling and normalization, exploratory data analyses, data distributions, correlograms, dimension reduction using PCA, SVD, K-means, SOM and t-SNE, machine leanring using PLA, SVM, DT, XgBoost, Naive Bayes, CNN etc.
BIO606 - Biostatistics
Set theory, Probability, Conditional probability and Bayes theorem, Descriptive statistics, Probability distributions (Binomial, Geometric, Normal, Pareto's, Poisson, Exponential, Gamma, Beta, Chi-square, t-distribution), Contgency tables and Chi-square test, Hypothesis testing, type I and II error, P-value, Power, parametric and non-parametric tests of signifcance, Linear regression, Correlation, Partial correlation, PCA, Causal inference
BIO401 - Genome Structure and Function
Review of Genome composition, GC and CpG content, Gene attributes, Promoter properties, DNA transposons & retrotransposons, piRNA, miRNAs, Linear organisation of genome, evolution of gene-clusters, Epigenetic modifications and 3D organisation of genome, Epigenetic reprogramming of genome during development and diseases, Genome technologies
BIO512 - Topics in Biology
Systems biology section: Introduction to scale-free networks, Gene regulatory networks, Hill's equation, Negative and positive Auto regulatory loops, Feed-forward, feed-back loops, oscillators etc.
IDC101 - Introduction to Computation (tutored)
Linux and Python
IDC620 - Computational Biology
Data-mining and Machine Learning section
IDC414 - Data Analysis using R
Introduction to R functions, data types and data structures, data import and export, programming in R, R-packages, statistics in R, data analysis and visualization, time series models, matrix algebra, dimension reduction, machine learning, optimization, network analysis, working with images.
IDC404 - Computational Genomics
IIntroduction to genes and genomes. Genome composition and complexity. Linear genome organization. Epigenetics. Three dimensional gneome organization. Genome technologies: sequencing, mapping, RNA-seq, GRO-seq, ChIP-seq, Repli-seq, 3C/4C/Hi-C. Differential gene expression analaysis. Gene/phenotype ontology analysis, pathway enrichment analysis, ChIP-seq Peak detection, domainogram analysis, 4C data analysis, Hi-C data analysis. Motif finding. Multi-variate analysis of genomics datasets, PCA, MFA, HMM/chromHMM, MDS, clustering techniques. Machine learning models in genomicsntroduction to R functions, data types and data structures, data import and export, programming in R, R-packages, statistics in R, data analysis and visualization, time series models, matrix algebra, dimension reduction, machine learning, optimization, network analysis, working with images.
BIO637 - Research Methodology
Philosophy of Science: What is science? Why do we do science? Why science is esteemed? Normative theories, Inductivism, Deductivism, Kuhn's Paradigm, Anarchistic theory, The design of Experiment: Fisher's method, hypothesis testing, Random and systematic errors, Confounders
BIO637 - Research Methodology
Introduction to bioinformatics, sequence analysis, systems biology