Zobrazeno 1 - 10
of 23
pro vyhledávání: '"SHANKAI YAN"'
Autor:
Ka-Chun Wong, Junyi Chen, Jiao Zhang, Jiecong Lin, Shankai Yan, Shxiong Zhang, Xiangtao Li, Cheng Liang, Chengbin Peng, Qiuzhen Lin, Sam Kwong, Jun Yu
Publikováno v:
iScience, Vol 15, Iss , Pp 332-341 (2019)
Summary: The early detection of cancers has the potential to save many lives. A recent attempt has been demonstrated successful. However, we note several critical limitations. Given the central importance and broad impact of early cancer detection, w
Externí odkaz:
https://doaj.org/article/8d6dac9870cf433bac646b466c96ee00
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 4, p e1007617 (2020)
A massive number of biological entities, such as genes and mutations, are mentioned in the biomedical literature. The capturing of the semantic relatedness of biological entities is vital to many biological applications, such as protein-protein inter
Externí odkaz:
https://doaj.org/article/672492f8e3f84727b53d4b19eac823a1
Autor:
Bin Zhang, Wenyong Dong, Chao Zhao, Meizhen Luo, Liangshun Wu, Shujun Yang, Juan Hu, Ling Peng, Shankai Yan
With the rapid growth of the text mining technology, knowledge discovery in text is appealing more and more to researchers. Furthermore, association rule mining (ARM), an essential issue in data mining, is widely used in the field of text information
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4fdbf9404958ebc679a973b0e94924ed
https://doi.org/10.21203/rs.3.rs-2946016/v1
https://doi.org/10.21203/rs.3.rs-2946016/v1
Autor:
Shankai Yan, Ka-Chun Wong
Publikováno v:
Future Generation Computer Systems. 117:111-124
DNA Computing is still at its infant stage since its emergence. Multiple aspects of DNA computing have been studied but most of the research results have not been applied to the reality. It has been proved to exhibit high data storage density and sup
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2924eb2b4324d49831d543895388bb2
https://doi.org/10.1016/j.future.2020.10.038
https://doi.org/10.1016/j.future.2020.10.038
Autor:
Zhiyong Lu, Rajarshi Ghosh, Daniel Veltri, Morgan Similuk, Andrew J. Oler, Shankai Yan, Ling Luo, Po-Ting Lai, Sandhya Xirasagar, Peter N. Robinson
Publikováno v:
Bioinformatics. 37:1884-1890
Automatic phenotype concept recognition from unstructured text remains a challenging task in biomedical text mining research. Previous works that address the task typically use dictionary-based matching methods, which can achieve high precision but s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9dc9add7b478e810dae5b3d0cff6a5e1
https://doi.org/10.1093/bioinformatics/btab019
https://doi.org/10.1093/bioinformatics/btab019
Autor:
Shankai Yan, Ling Luo, Po-Ting Lai, Daniel Veltri, Andrew J. Oler, Sandhya Xirasagar, Rajarshi Ghosh, Morgan Similuk, Peter N. Robinson, Zhiyong Lu
Publikováno v:
Journal of biomedical informatics. 129
The study aims at developing a neural network model to improve the performance of Human Phenotype Ontology (HPO) concept recognition tools. We used the terms, definitions, and comments about the phenotypic concepts in the HPO database to train our mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d46ccb9fd48b282906069c48877f3aa
https://pubmed.ncbi.nlm.nih.gov/35351638
https://pubmed.ncbi.nlm.nih.gov/35351638
Artificial Intelligence in Action: Addressing the COVID-19 Pandemic with Natural Language Processing
Publikováno v:
Annual review of biomedical data science. 4
The COVID-19 pandemic has had a significant impact on society, both because of the serious health effects of COVID-19 and because of public health measures implemented to slow its spread. Many of these difficulties are fundamentally information needs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::28cac7827a9ff5fbb9f87f93b9779311
https://pubmed.ncbi.nlm.nih.gov/34465169
https://pubmed.ncbi.nlm.nih.gov/34465169
Deleterious Non-Synonymous Single Nucleotide Polymorphism Predictions on Human Transcription Factors
Publikováno v:
IEEE/ACM Transactions on Computational Biology and Bioinformatics. 17:327-333
Transcription factors (TFs) are the major components of human gene regulation. In particular, they bind onto specific DNA sequences and regulate neighborhood genes in different tissues at different developmental stages. Non-synonymous single nucleoti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4efb5b8b601381c31076a45fe9affd8e
https://doi.org/10.1109/tcbb.2018.2882548
https://doi.org/10.1109/tcbb.2018.2882548
Publikováno v:
ACM Computing Surveys. 52:1-30
The recent advances in DNA sequencing technology, from first-generation sequencing (FGS) to third-generation sequencing (TGS), have constantly transformed the genome research landscape. Its data throughput is unprecedented and severalfold as compared
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73582914cf650c0b51053ce8a0f99c47
https://doi.org/10.1145/3340286
https://doi.org/10.1145/3340286