دورية أكاديمية
Leak Proof CMap; a framework for training and evaluation of cell line agnostic L1000 similarity methods ...
| العنوان: | Leak Proof CMap; a framework for training and evaluation of cell line agnostic L1000 similarity methods ... |
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| المؤلفون: | Shave, Steven, Kasprowicz, Richard, Athar, Abdullah M., Vlachou, Denise, Carragher, Neil O., Nguyen, Cuong Q. |
| بيانات النشر: | arXiv |
| سنة النشر: | 2024 |
| المجموعة: | DataCite Metadata Store (German National Library of Science and Technology) |
| مصطلحات موضوعية: | Quantitative Methods q-bio.QM, Machine Learning cs.LG, FOS Biological sciences, FOS Computer and information sciences |
| الوصف: | The Connectivity Map (CMap) is a large publicly available database of cellular transcriptomic responses to chemical and genetic perturbations built using a standardized acquisition protocol known as the L1000 technique. Databases such as CMap provide an exciting opportunity to enrich drug discovery efforts, providing a 'known' phenotypic landscape to explore and enabling the development of state of the art techniques for enhanced information extraction and better informed decisions. Whilst multiple methods for measuring phenotypic similarity and interrogating profiles have been developed, the field is severely lacking standardized benchmarks using appropriate data splitting for training and unbiased evaluation of machine learning methods. To address this, we have developed 'Leak Proof CMap' and exemplified its application to a set of common transcriptomic and generic phenotypic similarity methods along with an exemplar triplet loss-based method. Benchmarking in three critical performance areas (compactness, ... |
| نوع الوثيقة: | article in journal/newspaper report |
| اللغة: | unknown |
| DOI: | 10.48550/arxiv.2404.18960 |
| الإتاحة: | https://doi.org/10.48550/arxiv.2404.18960Test https://arxiv.org/abs/2404.18960Test |
| حقوق: | Creative Commons Attribution Share Alike 4.0 International ; https://creativecommons.org/licenses/by-sa/4.0/legalcodeTest ; cc-by-sa-4.0 |
| رقم الانضمام: | edsbas.74D37D8A |
| قاعدة البيانات: | BASE |
| DOI: | 10.48550/arxiv.2404.18960 |
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