公开(公告)号：US20230348994A1

公开(公告)日：2023-11-02

申请号：US18141167

申请日：2023-04-28

Applicant: Qatar Foundation for Education, Science and Community Development ,  Sidra Medicine

Inventor： Julie Valerie Caroline M Decock ,  Wouter Hendrickx ,  Raghvendra Mall

IPC: C12Q1/6886

CPC classification number: C12Q1/6886 ,  C12Q2600/178 ,  C12Q2600/158 ,  C12Q2600/112

Abstract: The present disclosure provides a method comprised of one or a combination of ir-lncRNA signatures to predict the clinical outcome of cancer patients, improve prognostic stratification of patients and guide cancer treatment decisions.

公开(公告)号：US20220392567A1

公开(公告)日：2022-12-08

申请号：US17804408

申请日：2022-05-27

Applicant: Qatar Foundation for Education, Science and Community Development

Inventor： Sanjay Chawla ,  Ehsan Ullah ,  Raghvendra Mall ,  Hossam Almeer ,  Abdurrahman Elbasir

IPC: G16B15/30 ,  G16B40/20 ,  A61K31/438 ,  G06N20/20

Abstract: A global effort is underway to identify compounds to treat emerging virus infections, such as COVID-19. Since de novo compound design is an extremely long, time-consuming, and expensive process, efforts are underway to discover existing compounds that can be repurposed for COVID-19 and new viral diseases. The present invention discloses a machine learning representation framework that uses deep learning-induced vector embeddings of compounds and viral proteins as features to predict compound-viral protein activity. The prediction model uses a consensus framework to rank approved compounds against viral proteins of interest.