Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Ammar Qaseem"'
Autor:
Kersten Döring, Ammar Qaseem, Michael Becer, Jianyu Li, Pankaj Mishra, Mingjie Gao, Pascal Kirchner, Florian Sauter, Kiran K Telukunta, Aurélien F A Moumbock, Philippe Thomas, Stefan Günther
Publikováno v:
PLoS ONE, Vol 15, Iss 3, p e0220925 (2020)
MOTIVATION:Much effort has been invested in the identification of protein-protein interactions using text mining and machine learning methods. The extraction of functional relationships between chemical compounds and proteins from literature has rece
Externí odkaz:
https://doaj.org/article/bd52bdcda3eb4a59ac2ec64f731edda5
Autor:
Yue Feng, Aurélien F. A. Moumbock, Dan Wang, Jianyu Li, Qianqing Xu, Ammar Qaseem, Stefan Günther
Publikováno v:
Journal of Chemical Information and Modeling. 61:5327-5330
While aromatic cages have extensively been investigated in the context of structural biology, molecular recognition, and drug discovery, there exist to date no comprehensive resource for proteins sharing this conserved structural motif. To this end,
Autor:
Stefan Günther, Ammar Qaseem
Publikováno v:
Bioinformatics (Oxford, England). 38(18)
Summary Newly discovered functional relationships of (bio-)molecules are a key component in molecular biology and life science research. Especially in the drug discovery field, knowledge of how small molecules associated with proteins plays a fundame
Autor:
Stefan Günther, Wolfgang Sippl, Ammar Qaseem, Kiran K. Telukunta, Conrad V. Simoben, Aurélien F. A. Moumbock, Fidele Ntie-Kang
Publikováno v:
Molecular Informatics
MOLECULAR INFORMATICS
MOLECULAR INFORMATICS
Medicinal plants have widely been used in the traditional treatment of ailments and have been proven effective. Their contribution still holds an important place in modern drug discovery due to their chemical, and biological diversities. However, the
Autor:
Kersten Döring, Stefan Günther, Kiran K. Telukunta, Michael Becer, Philippe Thomas, Ammar Qaseem
MotivationMuch effort has been invested in the identification of protein-protein interactions using text mining and machine learning methods. The extraction of functional relationships between chemical compounds and proteins from literature has recei
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b84a4238c3b1466e995fc2431eb5246e