Cancer Research Institute

About: Cancer Research Institute is a nonprofit organization based out in New York, New York, United States. It is known for research contribution in the topics: Cancer & Population. The organization has 1061 authors who have published 754 publications receiving 26712 citations.

Full-Length Genome Characterization of an HIV Type 2 Isolate from India

Abstract: An infectious Indian human immunodeficiency virus-2 (HIV-2) subtype A isolate was completely sequenced and analyzed and its phylogenetic relatedness was investigated The unusual limited size of the long terminal repeat (LTR) from the isolate was caused due to a truncation within the nef open reading frame (ORF) located at the U3 region of the LTR The genetic relatedness and lineage of this HIV-2 strain were investigated The close relatedness of this isolate to West African HIV-2 isolates confirms a geographical entry route of HIV-2 to this part of the Indian subcontinent This is the first report of an HIV-2 full genome analysis from the Indian subcontinent as well as from Asia

A phase II randomized control trial of erlotinib in combination with celecoxib in patients with operable oral squamous cell carcinoma (OSCC): Erlo-Xib Study.

Abstract: 6054Background: When combined with COX-2 inhibitors, the EGFR tyrosine kinase inhibitor Erlotinib has shown a better antitumor response in preclinical studies. Since high volume hospitals in many c...

Comprehensive Analysis of Low Molecular Weight Serum Proteome Enrichment for Mass Spectrometric Studies.

Abstract: Rationale: The low molecular weight (LMW) proteins present in circulating body fluids, such as serum and plasma, hold biological significance as possible biomarkers. A major obstacle in mass spectr...

Remodelling structure-based drug design using machine learning

Abstract: To keep up with the pace of rapid discoveries in biomedicine, a plethora of research endeavors had been directed toward Rational Drug Development that slowly gave way to Structure-Based Drug Design (SBDD) In the past few decades, SBDD played a stupendous role in identification of novel drug-like molecules that are capable of altering the structures and/or functions of the target macromolecules involved in different disease pathways and networks Unfortunately, post-delivery drug failures due to adverse drug interactions have constrained the use of SBDD in biomedical applications However, recent technological advancements, along with parallel surge in clinical research have led to the concomitant establishment of other powerful computational techniques such as Artificial Intelligence (AI) and Machine Learning (ML) These leading-edge tools with the ability to successfully predict side-effects of a wide range of drugs have eventually taken over the field of drug design ML, a subset of AI, is a robust computational tool that is capable of data analysis and analytical model building with minimal human intervention It is based on powerful algorithms that use huge sets of 'training data' as inputs to predict new output values, which improve iteratively through experience In this review, along with a brief discussion on the evolution of the drug discovery process, we have focused on the methodologies pertaining to the technological advancements of machine learning This review, with specific examples, also emphasises the tremendous contributions of ML in the field of biomedicine, while exploring possibilities for future developments