Validation and Topic-driven Ranking for Biomedical Hypothesis Generation Systems

Abstract

Literature underpins research, providing the foundation for new ideas. But as the pace of science accelerates, many researchers struggle to stay current. To expedite their searches, some scientists leverage hypothesis generation (HG) systems, which can automatically inspect published papers to uncover novel implicit connections. With no foreseeable end to the driving pace of research, we expect these systems will become crucial for productive scientists, and later form the basis of intelligent automated discovery systems. Yet, many resort to expert analysis to validate such systems. This process is slow, hard to reproduce, and takes time away from other researchers. Therefore, we present a novel method to validate HG systems, which both scales to large validation sets and does not require expert input. We also introduce a number of new metrics to automatically identify plausible generated hypotheses. Through the study of published, highly cited, and noise predicates, we devise a validation challenge, which allows us to evaluate the performance of a HG system. Using an in-progress system, MOLIERE, as a case-study, we show the utility of our validation and ranking methods. So that others may reproduce our results, we provide our code, validation data, and results at bit.ly/2EtVshN.

AI-based mining of biomedical literature: Applications for drug repurposing for the treatment of dementia

“…This facilitates the identification of intricate gene citations in scientific articles and books (41) and aids drug repurposing efforts (42,43). Previously we introduced literature mining methods (7,8,44) and demonstrated their potential application in many areas including the introduction of a new use for existing approved drug therapies (45). As a result of this project, a list of potential drugs for dementia treatment was extracted by AGATHA and advanced statistical analysis.…”

AI-based mining of biomedical literature: Applications for drug repurposing for the treatment of dementia

“…This facilitates the identi cation of intricate gene citations in scienti c articles and books (44) and aids drug repurposing efforts (45,46). Previously we introduced literature mining methods (7,8,47) and demonstrated their potential application in many areas including the introduction of a new use for existing approved drug therapies (48). As a result of this project, a list of potential drugs for dementia treatment was extracted by AGATHA and advanced statistical analysis.…”

Suppression of HIV and cocaine-induced neurotoxicity and inflammation by cell penetrable itaconate esters

“…Previously, we developed and applied a literature mining and transcriptomicsbased approach to uncover new compounds that can inhibit neurotoxic outcomes linked to both HIV and drugs of abuse, with the ultimate goal of identifying potential treatments for HAND with concurrent substance use disorders (Sybrandt, Shtutman et al 2017, Aksenova, Sybrandt et al 2019, Sybrandt, Tyagin et al 2020. The analysis of transcriptomes involved a well-established model that simulates HAND with comorbid cocaine use disorder (CUD), utilizing primary cortical cultures treated with Tat and cocaine (Turchan, Anderson et al 2001, Nath, Hauser et al 2002, Aksenov, Aksenova et al 2006, Midde, Huang et al 2013, Bertrand, Hu et al 2015, Aksenova, Sybrandt et al 2019.…”