Bioinformatics - Machine Learning and Network Medicine
Our bioinformatics research focusses on developing integrative translational informatics approaches. By integrating different data from varied sources onto one platform and connecting the nodes, we create a knowledgebase which can be used for better scientific, clinical and practical outcomes.
Current student projects:
Students are welcome to join specfic on-going or new pojects. Please mail to email@example.com
Minimum duration: 3 months
Fees: 5000 INR per month
Completed and ongoing projects:
1. In-Cardiome Knowledgebase: One of our main projects has been development of Inegrated Cardiome Knowledgebase for cardiovascular diseases (tri-incardiome.org).
2. Integrated Informatics Translational Platform: Translational informatics approaches are required for the integration of diverse and accumulating data to enable the administration of effective translational medicine specificially in complex diseases such as coronary artery disease (CAD).
3. BioParisodhana: Development of one platform for performing all the required bioinformatics analysis. Initially we tried to create interface which can link basic tools like BLAST, multiple alignment, primer design and restrictions enzyme digestion.
4. Diseasome networks of chromosome 12: Chromosomal mapping of disease data sets can help uncover important regulatory and functional links that may offer new insights for biomarker development.
We use biostatistics in performing data analysis of healthcare data from Ministry of Health, Government of India and World health Organization (WHO) in understanding the epidemiology of different diseases. Also in our earlier research we worked on Coronary Artery Disease in Indian population.
We will be glad to design new projects for students
1. Integrative gene ontology and network analysis of coronary artery disease associated genes suggests potential role of ErbB pathway gene EGFR. Mol Med Rop. 2018 Mar;17(3):4253-4264. doi:10.3892/mmr.2018.8393. Ghatge M, Nair J, Sharma A, Vangala RK
2. Danger-recognizing proteins, beta-defensin-128 and histatin-3 as potential biomarkkers of recurrent coronary events. Int J Mol Med. 2017 Aug;40(2):531-538. doi:10.3892/ijm.2017.3031. Ghatge M, Sharma A, Maity S, Kakkar VV, Vangala RK.
3. In-Cardiome: integrated knowledgebase for coronary artery disease enabling translational research. Database, Volume 2017, 1 January 2017, bax077, https://doi.org/10.1093/database/bax077 Ankit Sharma, Vrushali Deshpande, Madankumar Ghatge & Rajani Kanth Vangala
4. Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation. Mol Med Rep 2016 May;13(5):3904-12. doi:10.3892/mmr2016.5013 Sharma A, Ghatge M, Mundkur L, Vangala RK
5. Association of γ-glutamyl transferase with premature coronary artery disease. 2016 Mar;4(3):307-312. PubMed PMID: 26998267 PMCID: PMC4774353. Ghatge M, Sharma A and Vangala RK
6. Insights from Chromosome-Centric Mapping of Disease-Associated Genes: Chromosome 12 Perspective. Journal of Proteome Research. 2015 Sep 4;14(9):3432-40. doi: 10.1021/acs.jproteome.5b00488 Jayaram S, Gupta MK, Shivkumar BM, Ghatge M, Sharma A, Vangala RK, Sirdeshmukh R
7. BioParisodhana: A novel graphical interface integrating BLAST, ClustalW, primer3 adn restriction digestion tools. Bioinformation, 2012;8(13):639-43. doi: 10.6026/97320630008639. Vangala RK, Singh L, Gupta RP.
8. Novel network biomarkers profile based coronary artery disease risk stratification in Asian Indians. Adv Biomed Res 2013 Jul 30;2:59. doi: 10.4103/2277-9175.115805. Vangala RK, Ravindran C, Kamath K, Rao VS, Sridhara H
Computational Science & Artificial Intelligence:
1. Using support vector machine approach in creating Artificial Intelligence.
2. Using graph theory in network analysis in biomedicine and social media
3. Use of mobile phone image analysis for developing soil fertility app
Data Analytics: Big Data Analysis
1. Predictive analysis and tools for healthcare (risk prediction for diseases and help in improved disease monitoring)
2. Applying big data analysis in social media, market research and other fields
Use of computers, mobiles and other devices for human betterment. Presently we are working on using mobiles for improved healthcare.
Internet of Things (IoT):
Using IoT for better or smart life. We are currently working integrating several devices for smart home.
1. Developing next generation mobile technologies and to become the leader in applying AI in mobile phones.
2. Developing device free communication systems as next generation tele-communication (example: a 3D printed phone on skin to do 3D hologram projection visible only to one person who owns it)