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Showing 1–11 of 11 results

Advanced filters: Author: Tiffany J. Callahan Clear advanced filters

Association of post-COVID phenotypic manifestations with new-onset psychiatric disease

Ben Coleman
Elena Casiraghi
Peter N. Robinson
ResearchOpen Access08 Jun 2024
Translational Psychiatry

Volume: 14, P: 1-9
GRAPE for fast and scalable graph processing and random-walk-based embedding

GRAPE is a software resource for graph learning and embedding that is orders of magnitude faster than existing state-of-the-art libraries, making large-graph analysis feasible in a wide range of real-world applications.

Luca Cappelletti
Tommaso Fontana
Giorgio Valentini
ResearchOpen Access26 Jun 2023
Nature Computational Science

Volume: 3, P: 552-568
The GA4GH Phenopacket schema defines a computable representation of clinical data

Julius O. B. Jacobsen
Michael Baudis
Peter N. Robinson
Correspondence15 Jun 2022
Nature Biotechnology

Volume: 40, P: 817-820
Ontologizing health systems data at scale: making translational discovery a reality

Tiffany J. Callahan
Adrianne L. Stefanski
Michael G. Kahn
ResearchOpen Access19 May 2023
npj Digital Medicine

Volume: 6, P: 1-18
An open source knowledge graph ecosystem for the life sciences

Tiffany J. Callahan
Ignacio J. Tripodi
Lawrence E. Hunter
ResearchOpen Access11 Apr 2024
Scientific Data

Volume: 11, P: 1-22
Semantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discovery

Xingmin Aaron Zhang
Amy Yates
Peter N. Robinson
ResearchOpen Access02 May 2019
npj Digital Medicine

Volume: 2, P: 1-9
An ontology-based knowledge graph for representing interactions involving RNA molecules

Emanuele Cavalleri
Alberto Cabri
Marco Mesiti
ResearchOpen Access22 Aug 2024
Scientific Data

Volume: 11, P: 1-24
Unifying the identification of biomedical entities with the Bioregistry

Charles Tapley Hoyt
Meghan Balk
Benjamin M. Gyori
ResearchOpen Access19 Nov 2022
Scientific Data

Volume: 9, P: 1-13
Petagraph: A large-scale unifying knowledge graph framework for integrating biomolecular and biomedical data

Benjamin J. Stear
Taha Mohseni Ahooyi
Deanne M. Taylor
ResearchOpen Access18 Dec 2024
Scientific Data

Volume: 11, P: 1-28
At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods

Munib Mesinovic
Xin Ci Wong
David Zucman
ResearchOpen Access16 Jul 2024
Scientific Reports

Volume: 14, P: 1-43
ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

Ali Abbas
Sheryl Ann Abdukahil
Luis Felipe Reyes
ResearchOpen Access30 Jul 2022
Scientific Data

Volume: 9, P: 1-22