Dr. Pawar Shrikant


Pawar is an Assistant Professor (tenure-track) in Department of Computer Science and Biology at Claflin University. His research is focused on following broad topics:

1) Identifying cancer drug targets utilizing construction of complex interactome of proteins (article & article): The approach for CaI construction and analysis. (a) The three databases BIOCARTA, PID, REACTOME and KEGG utilised for the extraction of pathways followed by disintegration into protein constituents and identification of any other pathways they are involved with. (b) The meta database STRING for finding the interactions of all the proteins pooled above. (c) The large component of the CaI constructed from pooled interactions above, coloured by 335 modules by Rosvall Algorithm with node size plotted as per degree (d) The analyses for power law, K-core, inter- and intra-modular connectivities for CaI constructed followed by the drug statuses against centrality measures, in clockwise manner. The three SPINs and GPINs of A. baumannii reflecting the degree of connectivity. SPINs are represented in blue spheres connected through blue-colored curved lines for (A) VaCAB, having vaccine candidates; (B) ViFAB, with virulent factors; and (C) KeFAB, with key factors each with their interactors. (D) GPIN with proteins represented in black spheres connected with black curved lines to form the interactome. The technical analysis of the constructed CaI. (a) Complementary Cumulative Degree Distribution (CCDF) of CaI showing Power-Law behaviour. (b) K-core analysis of CaI representing the size of each k-shell (number of proteins appearing in k-core but not in k + 1th core) from periphery (k = 1) to inner core (k-max). (c) Classification of CaI proteins (R) based on its role and region in network space, the P-Z space classified into 7 categories of hub and non-hub nodes. The latter has been assigned as ultra-peripheral (R1), peripheral (R2), non-hub connector (R3) and non-hub kinless nodes (R4) and the former has been assigned as provincial (R5), connector (R6) and kinless hubs (R7) as described by Guimera et al. Kinless hubs nodes are supposed to be important in term of functionality, which has high connection within module as well as between modules.

2) Convolutional Neural Networks: Analysis of drug resistance from deep sequencing data (article). Restricted Boltzmann Machines are an effective machine learning tool for classification of genomic and structural data. They can also be used to compare resistance profiles of different protease inhibitors.

3) Prognostic Model Predicts Survival in Cancer Patients (article): An optimal prognostic model by the combination of six mRNAs was established. Kaplan–Meier survival analysis revealed effective risk stratification by this model for patients in the two datasets. The area under ROC curve (AUC) was > 0.65 for training and validation datasets, indicating good sensitivity and specificity of this model. Moreover, prominent superiority of this model to investigate prognostic biomarkers was demonstrated.

4) Regression and Tree Based Classification Models: Common cancer biomarkers identified through artificial intelligence (article). Identification of biomarker genes. (a) Heat map showing expression levels of top 25 cancer biomarker genes in ovarian and breast cancer types, (b) variable importance with gene ranks for all the genes, (c) mean decrease gini value for top 25 biomarker genes.

5) Deep Learning & Computer Vision: Bounding box algorithms are useful in localization of image patterns. Recently, utilization of convolutional neural networks on X-ray images has proven a promising disease prediction technique. However, pattern localization over prediction has always been a challenging task with inconsistent coordinates, sizes, resolution and capture positions of an image. In this article, we present a unique approach of SSD with a VGG-16 network as a backbone for feature detection of bounding box algorithm to predict the location of an anomaly within chest X-ray image (article & article):


  1. Doctor of Philosophy (Focused research: Bioinformatics): Georgia State University, Atlanta, Georgia, USA
  2. Master of Science (Focused research: Computer Science General): Georgia State University, Atlanta, Georgia, USA
  3. Master of Science (Focused research: Biology General): Georgia State University, Atlanta, Georgia, USA
  4. Master of Science (Focused research: Bioinformatics): Western Kentucky University, Bowling Green, Kentucky, USA
  • Doctoral Dissertation:
    Goal: Identifying newer bioinformatics techniques for studying drug resistance in HIV & Staphylococcus aureus. Dissertation published here.
  • Master’s Degree (Computer Science) Project:
    Goal: Computational optimization of defined graph-based sequence structure HIV-1 protease resistance prediction through supervised, unsupervised machine learning techniques.
  • Master’s Degree (Bioinformatics) Project:
    Goal: Transcriptomic data analysis to determine the impact of antioxidant supplementation on gene expression in brains of mice infected with T. gondii. Application of linear transformations like data driven Haar-Fisz transformations on microarray datasets for identifying gene expression trends.

Recent Publications


  1. Mapping subnational HIV mortality in six Latin American countries with incomplete vital registration systems publication BMC Medicine publication date January 8, 2021
  2. Hemoglobin induces early and robust biofilm development in Streptococcus pneumoniae by a pathway that involves comC but not the cognate comDE two-component system publication ASM Infection and Immunity publication date January 1, 2021
  3. Current clinical trials and patent update on lung cancer: a retrospective review publication Future Science Lung Cancer Management publication date 15 Feb 2021
  4. Sustainable Solutions for Overcoming Transportation and Pollution Problems in Smart Cities Springer Publication Advances in Sustainability Science and Technology publication date 15 March 2021
  5. Hearing loss prevalence and years lived with disability, 1990–2019: findings from the Global Burden of Disease Study 2019 Publication The Lancet Publication date March 13, 2021
  6. RNA-seq and miRNA-seq data from pharmacological inhibition of the G9a/GLP histone methyltransferase complex with UNC0642 in SAMP8 mice Publication Elsevier Data in Brief Publication date May 03, 2021
  7. Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019 Publication The Lancet Publication date May 27, 2021
  8. Spatial, temporal, and demographic patterns in prevalence of chewing tobacco use in 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019 Publication The Lancet Public Health Publication date May 27, 2021
  9. Subnational mapping of HIV incidence and mortality among individuals aged 15–49 years in sub-Saharan Africa, 2000–18: a modelling study Publication The Lancet HIV Publication date June 01, 2021
  10. G protein-coupled receptors as candidates for modulation and activation of the chemical senses in decapod crustaceans Publication Plos One Publication date June 04, 2021
  11. Measuring routine childhood vaccination coverage in 204 countries and territories, 1980–2019: a systematic analysis for the Global Burden of Disease Study 2020, Release 1 Publication The Lancet Publication date July 14 2021
  12. Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health: all-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019 Publication The Lancet Publication date Aug 17 2021
  13. Machine learning for identification and characterization of molecular gene signatures in progression of benign tumors Publication ACM Proceedings Publication date Aug 23 2021
  14. LinkedImm: a linked data graph database for integrating immunological data. Publication BMC Bioinformatics Publication date Aug 26 2021
  15. Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990–2050 Publication The Lancet Publication date Sep 23 2021 
  16. Techniques of Time Series Modeling in Complex Systems Publication Springer Lecture Notes in Networks and Systems Publication date Sep 24 2021
  17. Single shot detector application for image disease localization Publication bioRxiv Publication date Sep 24 2021
  18. Global, regional, and national sex differences in the global burden of tuberculosis by HIV status, 1990–2019: results from the Global Burden of Disease Study 2019 Publication The Lancet Infectious Diseases Publication date Sep 25 2021
  19. Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019 Publication The Lancet HIV Publication date Sep 27 2021
  20. Fatal police violence by race and state in the USA, 1980–2019: a network meta-regression Publication The Lancet Publication date Oct 1 2021
  21. Extracellular calcium alters calcium-sensing receptor network integrating intracellular calcium-signaling and related key pathway Publication NPG Scientific Reports Publication date Oct 19 2021
  22. Bioinformatics Algorithms and Software for Predicting Microbiomes Publication Springer Microbiome in Human Health and Disease Publication date Oct 21 2021
  23. Cyclical Learning Rates (CLR’s) for Improving Training Accuracies and Lowering Computational Cost Publication Research Square Publication data Dec 21 2021
  24. Hypoxia drives centrosome amplification in cancer cells via HIF-1α-dependent induction of polo-like kinase 4 Publication AACR Mol Cancer Res Publication date Dec 22 2021

Dr.  Pawar
Dr. Pawar Shrikant
Assistant Professor of Biology/Computer Science
  • School of Natural Sciences & Mathematics
James S. Thomas Science Building, Rm. 331
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