MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers

Frauds in scientific research and how to possibly overcome them

Frauds and misconduct have been common in the history of science. Recent events connected to the COVID-19 pandemic have highlighted how the risks and consequences of this are no longer acceptable. Two papers, addressing the treatment of COVID-19, have been published in two of the most prestigious medical journals; the authors declared to have analysed electronic health records from a private corporation, which apparently collected data of tens of thousands of patients, coming from hundreds of hospitals. Both papers have been retracted a few weeks later. When such events happen, the confidence of the population in scientific research is likely to be weakened. This paper highlights how the current system endangers the reliability of scientific research, and the very foundations of the trust system on which modern healthcare is based. Having shed light on the dangers of a system without appropriate monitoring, the proposed analysis suggests to strengthen the existing journal policies and improve the research process using new technologies supporting control activities by public authorities. Among these solutions, we mention the promising aspects of the blockchain technology which seems a promising solution to avoid the repetition of the mistakes linked to the recent and past history of research.

Geneshot: search engine for ranking genes from arbitrary text queries

The frequency by which genes are studied correlates with the prior knowledge accumulated about them. This leads to an imbalance in research attention where some genes are highly investigated while others are ignored. Geneshot is a search engine developed to illuminate this gap and to promote attention to the under-studied genome. Through a simple web interface, Geneshot enables researchers to enter arbitrary search terms, to receive ranked lists of genes relevant to the search terms. Returned ranked gene lists contain genes that were previously published in association with the search terms, as well as genes predicted to be associated with the terms based on data integration from multiple sources. The search results are presented with interactive visualizations. To predict gene function, Geneshot utilizes gene–gene similarity matrices from processed RNA-seq data, or from gene–gene co-occurrence data obtained from multiple sources. In addition, Geneshot can be used to analyze the novelty of gene sets and augment gene sets with additional relevant genes. The Geneshot web-server and API are freely and openly available from https://amp.pharm.mssm.edu/geneshot.