Precision Medicine

Precision medicine is changing the way we understand, diagnose and treat major life-threatening diseases. The transformation is driven by high-throughput molecular data that is being collected from patients, animal models, and large-scale cell line experiments. In this program, we will explore how the various -omics data types generated in these studies can be analyzed and integrated to study the basic biology associated with viruses & their hosts, cancer onset & development and outcomes.

Biomedical researchers now have access to more and more data. The data can provide new insight into the nature of diseases, drug therapies, treatment and even disease prevention. For diseases like cancer or those like the current viral epidemic - COVID19, these insights are vital to help both clinicians and researchers find better cures and develop new treatments. 

Key Topics Covered:

Next-Generation Sequencing and Big data analysis

Many types of omics data require step-by-step preparation, exploration, annotation, and visualization to understand. The T-BioInfo platform was designed for big multi-omics data analysis hiding the complexities of data with a user-friendly and intuitive interface that eliminates the need for coding and advanced machine learning algorithms for data integration and mining.

Application for Infectious Diseases

A program that embeds data-driven concepts into biological projects, spanning the student learning journey from observer to participant in research. Project-based learning for big data bioinformatics is to go beyond the theory with real datasets, projects, and expert mentors. Work with curated datasets from publicly available repositories with easy-to-follow tutorials.

Omics Data in Cancer Research

Data processing for Next Generation Sequencing, Mass-Spectroscopy, Structural and phenotypic data. Build and adapt pipelines using similar approaches to data mapping, quantification, and annotation that are used to prepare data for downstream statistical analysis, train machine learning models and annotate features.

Introduction to Programming: R and Python
Online bioinformatics coding exercises to learn and explore R and Python scripting and understand how to analyze and visualize -omics data to extract meaningful insights from large biological datasets. Learn, practice, and achieve bioinformatics greatness with concise exercises and interesting challenges right in the comfort of your browser!

Various areas of analysis in Precision Medicine

Precision Medicine In Immunology:

  • Will Host Genetics Affect the Response to SARS-CoV-2 Vaccines? Historical Precedents This paper discusses immunogenetic determinants of vaccine-induced immunity and the role of host genetics in response to SARS-CoV-2 vaccines. Link: 
  • Precision Vaccines: Lessons Learned from the Coronavirus Pandemic By Ofer Levy | TEDxBoston. In this talk, Dr. Levy discusses the application of precision medicine principles to vaccines and the lessons learned from applying these principles to the global pandemic.
  • Link:  

Precision Medicine In Neuroscience:

  • Application of Precision Medicine in Neurodegenerative Diseases 

Description: The paper discusses exploiting the data resulting from various -omic profiles such as epigenetics, pharmacogenetics, and microbiome can be used to develop stratified medicines for the patients. Link - 

  • Precision medicine in Parkinson’s disease: emerging treatments for genetic Parkinson’s disease

Description: The paper reviews clinical trials that target genetic forms of  GBA-associated and LRRK2-associated PD and the associated challenges that need to be overcome. Link - 

Precision Medicine For Health and Wellness:

  • Personalized Wellness Past and Future: Will the Science and Technology Coevolve?

This paper discusses personalized technologies such as tracking and monitoring devices, personalized nutrition services such as genetic testing kits, microbiome analyses, disease-focused services, and nutrition and fitness programs and briefly about the future of personalized wellness.Link: 

X-Omics in Oncology (Genomics, Transcriptomics, and Epigenetics):

Multi-omics profiling studies using genomics, epigenetics, transcriptomics, and proteomics approaches provide a comprehensive understanding of the molecular changes associated with diseases. For example, combining genomic and transcriptomic approaches can help understand disease mechanisms by annotating and prioritizing variants for functional analysis. Another good example is the combination of genomic and proteomic approaches that can reveal the functional impact of somatic mutations that contribute to tumor evolution and cancer progression.


Ethical Concerns In Precision Medicine:

  • Why Does the Shift from “Personalized Medicine” to “Precision Health” and “Wellness Genomics” Matter?

The paper highlights the importance of monitoring the growth of the precision medicine field. As the author discusses, there was first a transition from personalized to precision medicine. Then, from precision medicine, the field advances to precision health. And currently, the field is under transition from precision health to wellness genomics. The author highlights the ethical commitments associated with each of these transitions. Link:

Precision Medicine In Infectious Diseases:

  • Precision medicine in sepsis and septic shock: From omics to clinical tools description: The paper discusses the patient heterogeneity in sepsis and the various frameworks used for identification of these patients using sepsis, septic shock, and multiorgan dysfunction. Link: 


  • Implications of Using Host Response-Based Molecular Diagnostics on the Management of Bacterial and Viral Infections: A Review Description: The paper discusses the current use of host-based diagnostics for identifying infectious etiology, and respiratory infections (including SARS-COV-2, influenza, respiratory syncytial virus), mycobacterium tuberculosis, and sepsis. Link: 

Program Syllabus : Precision Medicine


1 (2)

Associated Coursework:

Session 1: Introduction To Bioinformatics For Precision Medicine

Topics to be covered:

  • Data Analysis: Combining Clinical and Molecular data
  • Molecular Data: Next-Generation Sequencing
  • From the Lab to the Clinic: Research, Discovery and
  • Clinical Use Cases
  • Case Studies in Precision Medicine


    Other Case Studies:

    • Herceptin cancer drug
    • Castration-resistant prostate cancer

2 (3)

Associated Example Project:

Session 2: Genomic Data Analysis 

Topics to be covered:

  • Introduction to Next Generation Sequencing (NGS): Genomic data
  • Analysis of NGS data and variant calling
  • Annotations of variants
  • Compare and contrasts:
  • germline and somatic mutations 
  • Identification of clinically relevant mutations

Associated Coursework:

      3 (2)


Associated Example Projects:

Session 3: Transcriptomic Data Analysis 

Topics to be covered:

  • Overview of RNA-seq data analysis
  • Read quality, pre-processing and mapping on reference genome using various tactics 
  • Quantification of genes and transcripts
  • Generating structured data, for biological interpretation
  • Unsupervised and supervised machine learning for gene expression data

Associated Coursework:

4 (1)


Associated Example Projects:

Session 4: Phylogenetic Analysis and Multiple Sequence Alignment (MSA)

Topics to be covered:

  • Phylogeny and MSA: Data preparation and analysis
  • Interpretation of outputs
  • Biological implications to identify variants of concern  or variants of interests
  • GWAS: Identification of resistant variants from a population
  • Development of multi-drug resistance in a pathogen infecting single host

Associated Coursework:

5 (1)


Session 5: Host Response to Infections

Topics to be covered:

  • Overview of infectious diseases
  • Pathogen strategies for exploitation of host cellular machinery
  • Host immune responses to infections
  • Identification of important activated immune elements
  • Development of effective therapies and treatments

Associated Example Projects:

Oncology Data Sources: Raw Data and Public Databases

Associated Example Project:

Session 6: Precision Medicine For Neuroscience

Topics to be covered:

  • Transcriptomics data for advanced stage Alzheimer’s disease (AD) 
  • Principal component analysis to explore trends
  • Differential gene expression analysis
  • Gene enrichment and Gene set enrichment analysis
  • Altered pathways in Alzheimer’s disease

7 (1)


Associated Coursework:

Session 7: Metagenomic Data Analysis

Topics to be covered:

  • Introduction to Metagenomic Sequencing 
  • 16S rRNA Gene Sequencing
  • Downstream analysis of 16S amplicon data using R
  • Metagenomics pipeline to study microbiome composition
  • DADA2 pipeline to understand microbial abundance

Associated Example Projects:


Associated RF Projects:

Session 8: Advancements in Precision Medicine

Topics to be covered:

  • Precision medicine case studies, publications, and datasets
  • Examples from oncology, neuroscience science, and infectious diseases
  • Literature review for developing an analysis plan 
  • Performing exploratory analysis, data processing, and preparation
  • Statistical analysis, biological interpretation, and validation.

Associated Resources:


Associated Resources:

Session 9: Oncology Data Sources: Raw Data and Public Databases

Topics to be covered:

  • Learn to retrieve cancer research data from public repositories:
  • Sequence Read Archive (SRA)  
  • Gene Expression Omnibus
  • Reference Sequence Database (RefSeq)
  • The Cancer Genome Atlas (TCGA)
  • Catalog Of Somatic Mutations In Cancer (COSMIC)


Session 10: Health, Wellness and Ethical Concerns 

Topics to be covered:

  • Personalized health and wellness technologies: tracking and monitoring devices
  • Personalized nutrition services: microbiome analyses, disease-focused services, nutrition programs
  • Future of personalized health and wellness
  • Ethical concerns in personalized health and wellness

Associated Resources:


NOTE : For interested participants in different time zones, the sessions will be recorded and made available to the registered cohort.

Register for the Precision Medicine Program

Case Studies for Precision Medicine




Project 14: Breast Cancer : Oncogene Variant Calling

Lesson 08 - Practical Understanding of Mutation Variant Analysis for TP53 gene

In this example project, we will learn to perform Mutation Variant Analysis for the TP53 gene in breast cancer data. 

Link to the dataset - 


Project 07: Changing Immune Response in Cancer

In this example project, we will perform transcriptomic profiling to understand changing immune responses. 

Link to dataset - 

Project 03: TCGA Liver Cancer - Precision Oncology  

Lesson 03 - Transcriptomics Signature for Tumor Stage Classification

In this example project, we will try to understand whether different tumor stage samples can be classified based on gene expression data of samples.

Links of Training and Test Dataset with Sample ID and with Clinical Phenotypes

Training set: 

Test set:


Project 11 - Surveillance of SARS-COV-2 VOC

In this example project, we will analyze UK sewage (waste) water samples to assess the SARS-COV-2 variants of concern.

Input data link: 

Severe acute respiratory syndrome coronavirus 2 isolate Wuhan-Hu-1, complete genome: 

Tuberculosis Infection And Treatment: Finding Variants In Mtb Genomic Data Associated With Drug Resistance



Project 10 - Host Response to Malaria Infection

In this example project, we will learn about modulation of host inflammatory responses to Plasmodium falciparum malarial infection based on Transcriptomics data.

Dataset link on GEO (GSE50957): 

Project 01: COVID-19 Origin & Pathogenesis of SARS-COV2

Lesson 06 - Transcriptional signature for Ruxolitinib treatment

Full original Data (GSE147507) with all treatments: 

Ruxolitinib (Rux) treated and untreated samples Data after removal of Zero values: 


Differentially Expressed Genes in Alzheimers

In this example project, we will explore transcriptomics data of advanced staged Alzheimer's Disease patients to identify what are the altered pathways. 

Dataset link on GEO (GSE53697): 


Project 13: Role of High Fat Diet on Obesity

In this example project, we will try to understand the microbial diversity after feeding a high fat and normal diet to mice and decipher its role in obesity and underlying diseases.

Zip file containing datasets - 

Project 16 Effect of Dietary Fiber Intake on Microbiome

High Dietary Fiber

NCBI Run Table:  


Lesson 04: Practical Hands-on DADA2 pipeline to understand microbial abundance

In this example project, we will run the DADA2 pipeline for Low Dietary Fiber (LDF) and High Dietary Fiber (HDF) groups separately to understand the microbial abundances of different conditions (pre and post intervention, where we will calculate the abundance before and after prebiotics intake) & sample type (prebiotics & placebo). 

Low Dietary Fiber 

NCBI Run Table: