bioRxivBioinformaticsPreprint
Cancer Cell Line Profiler (CCLP): a webserver for the prediction of compound activity across the NCI60 panel
Isidro Cortés‐CirianoiD, Daniel S MurrelliD, Bernard Chétrit, Andreas BenderiD, Thérèse E. MalliaviniD, Pedro J. BallesteriD
Abstract
SummaryCCLP (Cancer Cell Line Profiler) is a webserver for the prediction of compound activity across the NCI60 panel. CCLP uses a multi-task Random Forest model trained on 941,831 data-points that integrates structural information from 17,142 compounds and multi-omics data sets from 59 cancer cell lines. In addition, CCLP also implements conformal prediction to provide individual prediction errors at several confidence levels. CCLP computes compound descriptors for a set of input molecules and predicts their activity across the NCI60 panel. The output of running CCLP consists of one barplot per input compound displaying the predicted activities and errors across the NCI60 panel, as well as a text file reporting the predicted activities and errors in prediction\n\nAvailabilityCCLP is freely available on the web at cclp.marseille.inserm.fr
- Citations
- 4
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Knowledge-guided machine-learning and reverse screening combined method to predict cancer cell line responses to cytotoxic molecules
Alessandro Cuozzo, Marta A. S. Perez, … Vincent Zoete·bioRxiv·Dec 19, 2025
- Support Vector Machine based prediction models for drug repurposing and designing novel drugs for colorectal cancer
A. Sengupta, R. Kumar·bioRxiv·Oct 20, 2023
- Conformal prediction of molecule-induced cancer cell growth inhibition challenged by strong distribution shifts
Saiveth Hernandez-Hernandez, Qianrong Guo, Pedro J. Ballester·Pattern RecognitionPeer-reviewed·Apr 1, 2026
- Machine learning enables accurate and rapid prediction of active molecules against breast cancer cells
Shuyun He, Duancheng Zhao, … Ling Wang·Frontiers in PharmacologyPeer-reviewed·Dec 17, 2021
- Machine Learning-Based Drug Response Prediction Identifies Novel Therapeutic Candidates for Colorectal Cancer Cell Line KM-12
Cyrine Chanchabi, Conception Paul, … Michael Hahne·bioRxiv·Feb 24, 2025
- Predicting synergism of cancer drug combinations using NCI-ALMANAC data
Pavel Sidorov, Stefan Naulaerts, … Pedro J. Ballester·Frontiers in ChemistryPeer-reviewed·Jul 16, 2019