Zobrazeno 1 - 10
of 166
pro vyhledávání: '"Ozkirimli, Elif"'
Autor:
Temizer, Asu Büşra, Uludoğan, Gökçe, Özçelik, Rıza, Koulani, Taha, Ozkirimli, Elif, Ulgen, Kutlu O., Karalı, Nilgün, Özgür, Arzucan
Machine learning models have found numerous successful applications in computational drug discovery. A large body of these models represents molecules as sequences since molecular sequences are easily available, simple, and informative. The sequence-
Externí odkaz:
http://arxiv.org/abs/2210.14642
Motivation: The development of novel compounds targeting proteins of interest is one of the most important tasks in the pharmaceutical industry. Deep generative models have been applied to targeted molecular design and have shown promising results. R
Externí odkaz:
http://arxiv.org/abs/2209.00981
Autor:
Kulev, Igor, Köprü, Berkay, Rodriguez-Esteban, Raul, Saldana, Diego, Huang, Yi, La Torraca, Alessandro, Ozkirimli, Elif
The BioCreative VII Track 3 challenge focused on the identification of medication names in Twitter user timelines. For our submission to this challenge, we expanded the available training data by using several data augmentation techniques. The augmen
Externí odkaz:
http://arxiv.org/abs/2111.06664
Multi-label text classification is a challenging task because it requires capturing label dependencies. It becomes even more challenging when class distribution is long-tailed. Resampling and re-weighting are common approaches used for addressing the
Externí odkaz:
http://arxiv.org/abs/2109.04712
Coronavirus Disease of 2019 (COVID-19) created dire consequences globally and triggered an intense scientific effort from different domains. The resulting publications created a huge text collection in which finding the studies related to a biomolecu
Externí odkaz:
http://arxiv.org/abs/2009.02526
Text-based representations of chemicals and proteins can be thought of as unstructured languages codified by humans to describe domain-specific knowledge. Advances in natural language processing (NLP) methodologies in the processing of spoken languag
Externí odkaz:
http://arxiv.org/abs/2002.06053
Motivation: Prediction of the interaction affinity between proteins and compounds is a major challenge in the drug discovery process. WideDTA is a deep-learning based prediction model that employs chemical and biological textual sequence information
Externí odkaz:
http://arxiv.org/abs/1902.04166
Identification of high affinity drug-target interactions is a major research question in drug discovery. Proteins are generally represented by their structures or sequences. However, structures are available only for a small subset of biomolecules an
Externí odkaz:
http://arxiv.org/abs/1811.00761
Publikováno v:
In Drug Discovery Today
Publikováno v:
Bioinformatics 2018
The effective representation of proteins is a crucial task that directly affects the performance of many bioinformatics problems. Related proteins usually bind to similar ligands. Chemical characteristics of ligands are known to capture the functiona
Externí odkaz:
http://arxiv.org/abs/1801.10199