nference® launches first-in-class single cell RNA-sequencing resource to arm researchers fighting COVID-19 pandemic

– Developed in collaboration with Janssen, the Single Cell resource is being made available on the nferX® platform for free to academic researchers worldwide –

– Announcement follows nference joining the COVID-19 Healthcare Coalition, a private sector collaborative with Mayo Clinic, MIT Faculty and Health IT leaders, coordinated by MITRE –

nference today announced the launch of a first-in-class software resource that synthesizes disparate Single Cell RNA-sequencing (scRNA-seq) data sets to combat the COVID-19 public health crisis. The resource is equipped with the nferX augmented intelligence technology that teaches machines to comprehend over 100 million unstructured biomedical documents and triangulate these emergent insights from scientific literature with deep biological signals at single cell resolution.

By enabling researchers to study intricate molecular patterns and investigate the heterogeneity of healthy and pathologic tissues alike, the resource will help scientists to rapidly generate and pressure-test new hypotheses. The resource is envisioned to help researchers respond to the coronavirus outbreak, including decoding molecular signatures of viral infection, human-to-human transmission, and increased mortality risk from underlying health conditions or medication regimen. The nference Single Cell resource is free to all scientists in the academic community, including physicians and practitioners in academic medical centers.

“Single cell technology is a powerful lens for interrogating molecules that are linked to diseases. However, very few labs have the expert know-how needed to assimilate this data. Furthermore, realizing the full potential of single cell sequencing requires the derivation of reliable insights from the exponentially growing biomedical literature,” said Venky Soundararajan, Ph.D., Co-founder and Chief Scientific Officer of nference. “Our mission is to make the world’s biomedical knowledge computable, and with that comes the social responsibility to equip physicians and scientists with the tools needed to help mitigate the scourge of the COVID-19 pandemic.”

nference partnered with Janssen, through a broad data science effort that spans across therapeutic areas and functions. The Single Cell resource was developed by nference in-part to support Janssen’s discovery of novel therapeutic targets, including cancer sub-types with high unmet clinical need. The two companies also collaborated on a scientific paper published today by bioRxiv for rapid dissemination. The paper serves as a primer to instruct researchers on how to use the nference Single Cell resource.

Knowledge synthesis and the nferX Single Cell resource

rna-seq

(A) Knowledge synthesis: capturing association between concepts from over 100 million documents. Schematic shows the work-flow for generating literature-derived associations between phrases. Local score and global score are defined and the types of literature-derived associations are shown for combinations of high and low local and global scores. (B) Datasets enabling knowledge synthesis-powered scRNA-seq analysis platform. Single Cell RNAseq data was obtained from over 30 publicly available human and mouse single cell RNA-seq datasets. Bulk RNA-seq data was obtained from Gene Expression Omnibus (GEO) and the Genotype Tissue Expression (GTEx) project portal. Protein-level expression of coronavirus receptors was assessed using a collection of immunohistochemistry (IHC) images and tissue proteomics datasets from the Human Protein Atlas and the Human Proteome Map. Literature-derived association scores are obtained from over 100 million biomedical documents (C) Tissues and cell-types identified by one or more modalities to express ACE2, the putative receptor of SARS-CoV-2 spike protein.

The launch of the Single Cell resource by nference for academics worldwide comes following a call to action from the White House to the nation’s Artificial Intelligence (AI) experts to develop new natural language processing technologies that can be used to answer high-priority scientific questions related to the COVID-19 pandemic. nference also recently joined the COVID-19 Healthcare Coalition, coordinated by MITRE and first convened by the leaders of Mayo Clinic, Leavitt Partners and several Massachusetts Institute of Technology faculty leaders to form a powerful private sector collaborative that accelerates the development of secure, ethical, innovative, and open source solutions to address the COVID-19 public health crisis. In the spirit of this collaboration, the nference Single Cell resource is being made free to all scientists in the academic community, including physicians and practitioners in academic medical centers who are at the frontlines of fighting COVID-19 globally.

“We are pleased to have nference as a collaborator in the COVID-19 Health Coalition and this work illustrates the importance of using natural language processing and machine learning to turn unstructured data into actionable wisdom,” said John Halamka, M.D., President of the Mayo Clinic Platform.

Earlier this year, nference announced a strategic partnership with Mayo Clinic as its first Clinical Data Analytics Platform partner to accelerate drug discovery and development across the biopharmaceutical ecosystem to create cures for patients.

Source – BusinessWire

Venkatakrishnan AJ et al. (2020) Knowledge synthesis from 100 million biomedical documents augments the deep expression profiling of coronavirus receptors. bioRXiv [Epub ahead of print]. [ abstract]

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