In silico machine learning methods in drug developmentDobchev, Dimitar Atanasov; Pillai, Girinath Gopinathan; Karelson, MatiCurrent topics in medicinal chemistry2014 / p. 1913-1922

Rational design of a series of novel amphipathic cell-penetrating peptidesRegberg, Jakob; Srimanee, Artita; Dobchev, Dimitar A.; Karelson, MatiInternational journal of pharmaceutics2014 / p. 111-116 : ill

Subchronic oral and inhalation toxicities : a challenging attempt for modeling and predictionDobchev, Dimitar A.; Tulp, Indrek; Karelson, Gunnar; Tamm, Tarmo; Tämm, Kaido; Karelson, MatiMolecular informatics2013 / p. 793-801 : ill

Topological fingerprints as an aid in finding structural patterns for LRRK2 inhibitionKahn, Iiris; Lomaka, Andre; Karelson, MatiMolecular informatics2014 / p. 269-275 : ill

Toxicity profiling of 24 l-phenylalanine derived ionic liquids based on pyridinium, imidazolium and cholinium cations and varying alkyl chains using rapid screening Vibrio fischeri bioassayKusumahastuti, Dewi Kurnianingsih Arum; Sihtmäe, Mariliis; Kapitanov, Illia; Karpichev, Yevgen; Gathergood, Nicholas; Kahru, AnneEcotoxicology and environmental safety2019 / p. 556-565 : ill https://doi.org/10.1016/j.ecoenv.2018.12.076 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

Using artificial neural networks to predict cell-penetrating compoundsKarelson, Mati; Dobchev, DimitarExpert opinion drug discovery2011 / p. 783-796 : ill