The next-generation Open Targets Platform: reimagined, redesigned, rebuilt

D Ochoa, A Hercules, M Carmona… - Nucleic acids …, 2023 - academic.oup.com
Abstract The Open Targets Platform (https://platform. opentargets. org/) is an open source
resource to systematically assist drug target identification and prioritisation using publicly …

Knowledge graph-based recommendation framework identifies drivers of resistance in EGFR mutant non-small cell lung cancer

A Gogleva, D Polychronopoulos, M Pfeifer… - Nature …, 2022 - nature.com
Resistance to EGFR inhibitors (EGFRi) presents a major obstacle in treating non-small cell
lung cancer (NSCLC). One of the most exciting new ways to find potential resistance …

Democratizing knowledge representation with BioCypher

S Lobentanzer, P Aloy, J Baumbach, B Bohar… - Nature …, 2023 - nature.com
Biomedical data are amassed at an ever-increasing rate, and machine learning tools that
use prior knowledge in combination with biomedical big data are gaining much traction 1, 2 …

Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque

A Fernández-Torras, M Duran-Frigola, M Bertoni… - Nature …, 2022 - nature.com
Biomedical data is accumulating at a fast pace and integrating it into a unified framework is a
major challenge, so that multiple views of a given biological event can be considered …

EMBL's European bioinformatics Institute (EMBL-EBI) in 2022

M Thakur, A Bateman, C Brooksbank… - Nucleic Acids …, 2023 - academic.oup.com
Abstract The European Molecular Biology Laboratory's European Bioinformatics Institute
(EMBL-EBI) is one of the world's leading sources of public biomolecular data. Based at the …

Text-to-text extraction and verbalization of biomedical event graphs

G Frisoni, G Moro, L Balzani - Proceedings of the 29th …, 2022 - aclanthology.org
Biomedical events represent complex, graphical, and semantically rich interactions
expressed in the scientific literature. Almost all contributions in the event realm orbit around …

Moomin: Deep molecular omics network for anti-cancer drug combination therapy

B Rozemberczki, A Gogleva, S Nilsson… - Proceedings of the 31st …, 2022 - dl.acm.org
We propose the molecular omics network (MOOMIN) a multimodal graph neural network
used by AstraZeneca oncologists to predict the synergy of drug combinations for cancer …

Integrating knowledge graphs into machine learning models for survival prediction and biomarker discovery in patients with non–small-cell lung cancer

C Fang, GA Arango Argoty, I Kagiampakis… - Journal of Translational …, 2024 - Springer
Accurate survival prediction for Non-Small Cell Lung Cancer (NSCLC) patients remains a
significant challenge for the scientific and clinical community despite decades of advanced …