Zobrazeno 1 - 10
of 89
pro vyhledávání: '"Shunfang Wang"'
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-16 (2021)
Abstract Background At present, the bioinformatics research on the relationship between aging-related diseases and genes is mainly through the establishment of a machine learning multi-label model to classify each gene. Most of the existing methods f
Externí odkaz:
https://doaj.org/article/4cf03adf0490425baa4d9f124f9a68e9
Publikováno v:
BMC Bioinformatics, Vol 22, Iss S3, Pp 1-21 (2021)
Abstract Background Antifreeze proteins (AFPs) are a group of proteins that inhibit body fluids from growing to ice crystals and thus improve biological antifreeze ability. It is vital to the survival of living organisms in extremely cold environment
Externí odkaz:
https://doaj.org/article/379e1343326d4b76b5a785360aee3cf2
Autor:
Hao Shao, Shunfang Wang
Publikováno v:
Entropy, Vol 25, Iss 5, p 727 (2023)
Recently, there has been a rapid increase in deep classification tasks, such as image recognition and target detection. As one of the most crucial components in Convolutional Neural Network (CNN) architectures, softmax arguably encourages CNN to achi
Externí odkaz:
https://doaj.org/article/caad82b0a5dc413598cbf061e8b82d3d
Publikováno v:
BMC Genomics, Vol 21, Iss 1, Pp 1-14 (2020)
Abstract Background Antimicrobial resistance is one of our most serious health threats. Antimicrobial peptides (AMPs), effecter molecules of innate immune system, can defend host organisms against microbes and most have shown a lowered likelihood for
Externí odkaz:
https://doaj.org/article/586c77b8432c4d92a4f1d7b1e7211bc3
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S25, Pp 1-17 (2019)
Abstract Background Membrane proteins play an important role in the life activities of organisms. Knowing membrane protein types provides clues for understanding the structure and function of proteins. Though various computational methods for predict
Externí odkaz:
https://doaj.org/article/9b00347a5af645f49be23827980609a3
Autor:
Shunfang Wang, Xiaoheng Wang
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S25, Pp 1-17 (2019)
Abstract Background Protein structural class predicting is a heavily researched subject in bioinformatics that plays a vital role in protein functional analysis, protein folding recognition, rational drug design and other related fields. However, whe
Externí odkaz:
https://doaj.org/article/04f54e2e8c464e47a9519b8803547044
Publikováno v:
IEEE Access, Vol 7, Pp 42384-42395 (2019)
This paper proposes an improved protein feature expression called segmented amino acid composition in position-specific scoring matrix (PSSM-SAA) in the field of subcellular localization prediction. Since there has been sufficient local information i
Externí odkaz:
https://doaj.org/article/8b6d1a2a54c84da184661f29cae97d2d
Publikováno v:
IEEE Access, Vol 6, Pp 75669-75681 (2018)
Membrane proteins occupy an important position in the life activities of humans and other species. The elucidation of membrane protein types provides clues for understanding the structure and function of proteins. With the fusion of various protein i
Externí odkaz:
https://doaj.org/article/7f4e1ad267d74f05b77c488f391d20d4
Autor:
Shunfang Wang, Shuhui Liu
Publikováno v:
International Journal of Molecular Sciences, Vol 16, Iss 12, Pp 30343-30361 (2015)
An effective representation of a protein sequence plays a crucial role in protein sub-nuclear localization. The existing representations, such as dipeptide composition (DipC), pseudo-amino acid composition (PseAAC) and position specific scoring matri
Externí odkaz:
https://doaj.org/article/0c1d3f42bde44bb48e383b53ddc81418
Autor:
Shunfang Wang, Yaoting Yue
Publikováno v:
PLoS ONE, Vol 13, Iss 4, p e0195636 (2018)
A wide variety of methods have been proposed in protein subnuclear localization to improve the prediction accuracy. However, one important trend of these means is to treat fusion representation by fusing multiple feature representations, of which, th
Externí odkaz:
https://doaj.org/article/3783700364e540638f217cd872b50496