Results 111 to 120 of about 123,989 (167)

MetaPredictor: in silico prediction of drug metabolites based on deep language models with prompt engineering. [PDF]

Brief Bioinform
Zhu K, Huang M, Wang Y, Gu Y, Li W, Liu G, Tang Y.   +6 more
europepmc   +1 more source

Strategy advancements in placental pharmacokinetics: from <i>in vitro</i> experiments to <i>in silico</i> prediction. [PDF]

Front Pharmacol
Li Z, Wu Y, Zeng S, Wang F, Zhang J, Li S, Yang Y, Yang Y.   +7 more
europepmc   +1 more source

In silico prediction of polyketide biosynthetic gene clusters in the genomes of Hypericum-borne endophytic fungi. [PDF]

BMC Genomics
Petijová L, Henzelyová J, Kuncová J, Matoušková M, Čellárová E.   +4 more
europepmc   +1 more source

Potential of Indole-3-Carbinol compounds from broccoli (<i>Brassica oleracea var. italica</i>) as natural aromatase blockers: In silico prediction and <i>in vivo</i> studies. [PDF]

Open Vet J
Amalia R, Ohama T, Parhar IS, Airin CM, Sato H, Budiyanto A, Astuti P.   +6 more
europepmc   +1 more source

<i>In silico</i> prediction of paradoxical effect for oxaliplatin in gastric cancer patients based on their transcriptomic profile. [PDF]

Res Pharm Sci
Khara F, Heydari A, Fadaie M, Khalafiyan A, Khanahmad H.   +4 more
europepmc   +1 more source

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Comparison of In Silico Models for Prediction of Mutagenicity

Journal of Environmental Science and Health, Part C: Environmental Carcinogenesis and Ecotoxicology Reviews, 2013
Using a dataset with more than 6000 compounds, the performance of eight quantitative structure activity relationships (QSAR) models was evaluated: ACD/Tox Suite, Absorption, Distribution, Metabolism, Elimination, and Toxicity of chemical substances (ADMET) predictor, Derek, Toxicity Estimation Software Tool (T.E.S.T.), TOxicity Prediction by Komputer ...
Todd Martin, Giuseppa Raitano, Emilio Benfenati   +2 more
exaly   +3 more sources

In silico prediction of clinical efficacy

Current Opinion in Biotechnology, 2006
Drug development is a high risk and costly process, and the ability to predict clinical efficacy in silico (in a computer) can save the pharmaceutical industry time and resources. Additionally, such an approach will result in more targeted, personalized therapies.
Seth, Michelson, Anil, Sehgal, Christina, Friedrich   +2 more
openaire   +2 more sources

In Silico Prediction of Allergenic Proteins

2014
Currently, the prediction of new allergens is becoming important due to use of genetically modified (GM) foods and biopharmaceuticals. In this chapter, we describe how to use four popular allergenic prediction servers: (1) Structural Database of Allergenic Proteins (SDAP), (2) Allermatch, (3) Evaller 2, and (4) AlgPred. The first two prediction servers
Gaurab, Sircar, Bodhisattwa, Saha, Swati Gupta, Bhattacharya, Sudipto, Saha   +3 more
openaire   +2 more sources

In Silico Prediction of Permeability Coefficients

2021
In silico simulations of biological systems are of the significant importance to obtain insights on specific processes that experimental protocols have difficulty to elucidate. More particularly, and to ensure that a given molecule is able to reach its cellular target, the development of computational methods able to quickly estimate the cellular ...
openaire   +2 more sources

In silico prediction of genotoxicity

Food and Chemical Toxicology, 2017
The in silico prediction of genotoxicity has made considerable progress during the last years. The main driver for the pharmaceutical industry is the ICH M7 guideline about the assessment of DNA reactive impurities. An important component of this guideline is the use of in silico models as an alternative approach to experimental testing.
openaire   +2 more sources