Drug ranking - OmicsDI

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CHEBI ID

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Metabolite Name

PC(30:1) (1)
DG(40:4) (1)
DG(40:5) (1)
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DG(38:0) (1)
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PC(36:0) (1)

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Modelling Approach

Regression method (1)
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Lab affiliation

Centre for Applied Pharmacokinetic Research, School of Health Sciences, The University of Manchester, UK (4)
Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center Amsterdam, OncoProteomics Laboratory, Amsterdam, Netherlands (2)
1 - College of Pharmacy, University of Sharjah, Sharjah 2 - Sharjah Institute for Medical Research, University of Sharjah, Sharjah (1)
1- Department of Biology, Faculty of Science, Erciyes University, Kayseri, Turkey 2- Genome and Stem Cell Center (GENKÖK) Erciyes University, Kayseri, Turkey (1)
Barts Cancer Institute. Queen Mary University of London (1)
Boehringer Ingelheim Pharma GmbH & Co. KG, Drug Discovery Sciences (1)
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Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, School of Health Sciences, Stopford Building, Room 2.026, Oxford Road, Manchester, M13 9PT. (1)
Centre for Applied Pharmacokinetic Research, School of Health Sciences, The University of Manchester (1)
Department of Clinical Sciences Lund, Section of Oncology, Lund University, Lund 221 85, Sweden (1)
Department of Neurobiology, School of Biology/Chemistry, Osnabrück University, Germany. Center for Cellular Nanoanalytics, Osnabrück University, Germany. Institute of Cognitive Science, Osnabrück University, Germany. (1)
Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne (1)
Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia (1)
Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Victoria, Australia (1)
Division of Pediatric Hematology and Oncology, Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Switzerland (1)
Eye & Vison Health, Flinders University School of Medicine Flinders Medical Center Flinders University Australia (1)
INEPCP FRCCP RAS, Moscow, Russia (1)
Montana State University, Department of Microbiology and Cell Biology, Bozeman, MT (1)
OncoProteomics Laboratory, Dept of Medical Oncology, VU University Medical Center, Amsterdam, The Netherlands (1)
Pedro R. Cutillas Professor of Cell Signalling & Proteomics Centre for Genomics and Computational Biology Barts Cancer Institute Queen Mary, University of London John Vane Science Centre, Charterhouse Square, London EC1M 6BQ (1)
Robert Lieberman Endowed Professor of Anesthesiology University of Nebraska Medical Center College of Medicine, Department of Anesthesiology (1)
Section for Translational Surgical Oncology and Biobanking, Department of Surgery, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Germany (1)
TU München Lehrstuhl Organische Chemie II Department of Chemistry Lichtenbergstr. 4 85747 Garching bei München (1)
Transplantation Center, the Third Xiangya Hospital, Central South University, Changsha, Hunan, China (1)
University of Rome Tor Vergata (1)

IsPrivate

False (3)

Model Flag

Non Kinetic (1)

Submitter Keywords

Ersilia (1)
FAIR-AIML (1)
Machine Learning Model (1)
TransQST (1)

Classification

bacteria (1)

Study type

Transcription profiling by array (23)
RNA-seq of coding RNA (7)
DNA-seq (2)
Other (1)
Methylation profiling by array (1)
RNA-seq of coding RNA from single cells (1)

Release Date

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2005 (2)
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2001 (1)

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Machine learning from large-scale proteomics accurately ranks anti-cancer drugs based on efficacy

We present an approach, named Drug Ranking Using ML (DRUML), which uses omics data to produce ordered lists of > 400 drugs based on their effectiveness in decreasing cancer cell proliferation. We trained and validated DRUML using in-house proteomics and phosphoproteomics data from a panel of 26 AML,...

ORGANISM(S): Homo sapiens (Human)

2021-02-22 | PXD019591 | Pride

Computational analysis of cholangiocarcinoma phosphoproteomes identifies patient-specific drug targets

We used mass-spectrometry based phosphoproteomics and computational methods to identify patient-specific drug targets in primary CCA and CCA-derived cell lines. We analyzed 13 primary CCA with matched background tissue and 8 different cell lines leading to the identification and quantification of >1...

ORGANISM(S): Homo sapiens (Human)

2023-03-11 | PXD027329 | Pride

Cholangiocarcinoma

The New Zealand drug harms ranking study: A multi-criteria decision analysis.

Not available

S-EPMC10481626 | biostudies-literature

Blood transcriptomics of drug-naive sporadic Parkinson'?s disease patients

Parkinson's disease (PD) is a chronic progressive neurodegenerative disorder that is clinically defined in terms of motor symptoms. These are preceded by prodromal non-motor manifestations that prove the systemic nature of the disease. Identifying genes and pathways altered in living patients provid...

ORGANISM(S): Homo sapiens

2015-10-29 | E-GEOD-72267 | biostudies-arrayexpress

Iterative sure independent ranking and screening for drug response prediction.

Not available

S-EPMC7507262 | biostudies-literature

Chemical-induced gene expression ranking and its application to pancreatic cancer drug repurposing.

Not available

S-EPMC9023899 | biostudies-literature

Enhanced ranking of PknB Inhibitors using data fusion methods.

Not available

S-EPMC3600029 | biostudies-literature

A method for systematically ranking therapeutic drug candidates using multiple uncertain screening criteria.