M
Mahyuddin K. M. Nasution
Researcher at University of North Sumatra
Publications - 119
Citations - 860
Mahyuddin K. M. Nasution is an academic researcher from University of North Sumatra. The author has contributed to research in topics: Computer science & Social network. The author has an hindex of 13, co-authored 97 publications receiving 600 citations. Previous affiliations of Mahyuddin K. M. Nasution include National University of Malaysia.
Papers
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Journal ArticleDOI
A deep insight into CRISPR/Cas9 application in CAR-T cell-based tumor immunotherapies.
Ehsan Razeghian,Mahyuddin K. M. Nasution,Heshu Sulaiman Rahman,Heshu Sulaiman Rahman,Zhanna R. Gardanova,Walid Kamal Abdelbasset,Walid Kamal Abdelbasset,Surendar Aravindhan,Dmitry Bokov,Wanich Suksatan,Pooria Nakhaei,Siavash Shariatzadeh,Faroogh Marofi,Mahboubeh Yazdanifar,Somayeh Shamlou,Roza Motavalli,Farhad Motavalli Khiavi +16 more
TL;DR: In this paper, a brief overview of the CAR-T cell application in the context of tumor immunotherapy is presented, with a special focus on CRISPR-Cas9 technology.
Proceedings ArticleDOI
Extraction of academic social network from online database
TL;DR: The use of association rule is demonstrated to enhance existing superficial method for extracting social network from online database such as the DBLP and has shown the capacity to extract social relation as well as the strength of these relations.
Book ChapterDOI
Superficial method for extracting social network for academics using web snippets
TL;DR: This paper demontrate the possibility of exploiting features in Web snippets returned by search engines for disambiguating entities and building relations among entities during the process of extracting social networks.
Posted Content
Information Retrieval Model: A Social Network Extraction Perspective
TL;DR: A model of information retrieval from the social network extraction is proposed and preferably incorporate the probability theory for assigning the semantic.
Proceedings ArticleDOI
Information retrieval model: A social network extraction perspective
TL;DR: In this paper, a model of information retrieval from the social network extraction is proposed, which incorporates the probability theory for assigning the semantic for assigning a semantic to the content descriptions generated by social network extractors.