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<strong>PTML Model Prediction of Preclinical Activity</strong>

Harbil Bediaga, Sonia Arrasate Gil

Proceedings of MOL2NET 2018, International Conference on Multidisciplinary Sciences, 4th edition(2018)

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Abstract
ChEMBL-tik datu basea lortuta, perturbazio teoria (PT) eta Machine Learning (ML) teknikak erabilita PTML eredu bat eraiki da, zein sistema biomolekular konplexuetan erabili daitekeen perturbazioen efektua kuantifikatzeko. Eredu hau erabilita konposatu berri batek erakusten dituen minbiziaren aurkako parametro klinikoen (ki, LD50, etab.) balioak aurresan ditzakegu. After obtaining the database from ChEMBL we combine Perturbation Theory (PT) and Machine Learning (ML) to obtain PTML Model, which has been created to quantify the perturbations of complex bio molecular systems. The model can predict preclinical (ki, LD50, etc.) values of new anti-cancer compounds.
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Drug Target Identification
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