Rajiv Karbhal PhD.
Dr. Rajiv Karbhal is the Technical Lead for Vgenomics. He completed his Masters and PhD. in Bioinformatics from Savitribai Phule Pune University. In his professional career, he has traveled to Germany to join the Institute of Environmental Medicine in Augsburg as a Bioinformatics and IT officer.
Here he developed both his professional skill and interest in using AI in the digital realm. Dr. Karbhal believes that Artificial Intelligence plays a transformative role in revolutionizing the landscape of Digital Health, enhancing patient care, and driving efficiencies across the healthcare industry. He notes that by leveraging AI algorithms and machine learning techniques, healthcare providers can analyze vast amounts of medical data to derive valuable insights for personalized treatment plans, early disease detection, and predictive analytics. AI-powered systems can assist healthcare professionals in diagnosing diseases more accurately and swiftly, leading to improved patient outcomes.
According to Dr. Karbhal, the integration of AI in Digital Health not only enhances clinical decision-making but also improves operational efficiencies, reduces healthcare costs, and ultimately transforms the way healthcare is delivered and experienced. His beliefs and experience are core to his role as Technical Lead here at Vgenomics.
Research articles
Dr. Karbhal’s research revolves around tRNA expression and Transcriptome manipulation.
AllerBase: a comprehensive allergen knowledgebase
Allergic diseases represent a major health concern worldwide due to steady rise in their prevalence leading to increased disease burden. The field of allergy research has witnessed significant progress and the focus of studies has shifted to molecular level. Vast amounts of data for allergens are archived in allergen databases, which cover diverse aspects of allergens and allergenicity with varying degrees of completeness. Users are required to refer to multiple databases including…
Antibody class (es) predictor for epitopes (AbCPE): A multi-label classification algorithm
Development of vaccines and therapeutic antibodies to deal with infectious and other diseases are the most perceptible scientific interventions that have had huge impact on public health including that in the current Covid-19 pandemic. From inactivation methodologies to reverse vaccinology, vaccine development strategies of 21st century have undergone several transformations and are moving towards rational design approaches. These developments are driven by data as the combinatorials involved in antigenic diversity of pathogens and immune…
BioDB extractor: customized data extraction system for commonly used bioinformatics databases
Diverse types of biological data, primary as well as derived, are available in various formats and are stored in heterogeneous resources. Database-specific as well as integrated search engines are available for carrying out efficient searches of databases. These search engines however, do not support extraction of subsets of data with the same level of granularity that exists in typical database entries. In order to extract fine grained subsets of data, users are required to download complete or partial database entries and write scripts for parsing and extraction…
iCEED: Integrated Customized Extraction of Enzyme Data
Enzymes catalyse diverse biochemical reactions and are building blocks of cellular and metabolic pathways. Data and metadata of enzymes are distributed across databases and are archived in various formats. The enzyme databases provide utilities for efficient searches and downloading enzyme records in batch mode but do not support organism-specific extraction of subsets of data. Users are required to write scripts for parsing entries for customised data extraction prior to downstream analysis. Integrated Customized Extraction of Enzyme Data (iCEED) has been developed to provide…
PFV3D: Protein Feature Visualisation on 3D structure
Mapping and Visualisation of various sequence-based features of proteins on the three dimensional (3D) structure enables to connect the sequence-space to the structure-space and thereby facilitates understanding of the sequence-structure-function relationship of proteins. Academic and commercial software programs are available for visualization and rendering of 3D structures but lack utilities for selection, customization, and integration of data from UniProt and PDB. PFV3D addresses these gaps and enables visualisation of features on the 3D structure using the JSmol applet…
