Zobrazeno 1 - 10
of 136
pro vyhledávání: '"Zhiqiang Pang"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract The wide applications of liquid chromatography - mass spectrometry (LC-MS) in untargeted metabolomics demand an easy-to-use, comprehensive computational workflow to support efficient and reproducible data analysis. However, current tools wer
Externí odkaz:
https://doaj.org/article/7e61ad1eb5564c24baf3c082e2a1737e
Publikováno v:
PLoS Computational Biology, Vol 20, Iss 6, p e1011912 (2024)
To standardize metabolomics data analysis and facilitate future computational developments, it is essential to have a set of well-defined templates for common data structures. Here we describe a collection of data structures involved in metabolomics
Externí odkaz:
https://doaj.org/article/9e39222fa6d9460a9f0042e59533afb4
Publikováno v:
Carbohydrate Polymer Technologies and Applications, Vol 7, Iss , Pp 100522- (2024)
Lithium bromide molten salt hydrate (∼62 wt% aqueous solution of LiBr) can dissolve cellulose, but the cellulose dissolution mechanisms are not fully understood. This study revisited cellulose dissolution in the LiBr solution and aimed to provide n
Externí odkaz:
https://doaj.org/article/c93848c2bc0541678f523556d5e7b980
Autor:
Meredith Sherrill, Alexandre Bernier-Graveline, Jessica Ewald, Zhiqiang Pang, Michel Moisan, Mathieu Marzelière, Maris Muzzy, Tracy A. Romano, Robert Michaud, Jonathan Verreault
Publikováno v:
Frontiers in Marine Science, Vol 11 (2024)
The St. Lawrence Estuary (SLE) belugas (Quebec, Canada) are an endangered population whose numbers remain low despite ongoing conservation efforts. Multiple anthropogenic factors and changing environmental conditions are thought to have contributed t
Externí odkaz:
https://doaj.org/article/f33a972aef264a91b0207c7dc0a100df
Autor:
Peng Liu, Jessica Ewald, Zhiqiang Pang, Elena Legrand, Yeon Seon Jeon, Jonathan Sangiovanni, Orcun Hacariz, Guangyan Zhou, Jessica A. Head, Niladri Basu, Jianguo Xia
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-11 (2023)
Abstract The increasing application of RNA sequencing to study non-model species demands easy-to-use and efficient bioinformatics tools to help researchers quickly uncover biological and functional insights. We developed ExpressAnalyst ( www.expressa
Externí odkaz:
https://doaj.org/article/64d4f683e1c34283bcfe80032d089e14
Autor:
Yubo Hu, Zhiqiang Pang
Publikováno v:
PLoS ONE, Vol 19, Iss 5, p e0303042 (2024)
Probabilistic hesitant fuzzy sets (PHFSs) are superior to hesitant fuzzy sets (HFSs) in avoiding the problem of preference information loss among decision makers (DMs). Owing to this benefit, PHFSs have been extensively investigated. In probabilistic
Externí odkaz:
https://doaj.org/article/bd5fe5a6348b4a4a9152e6cf93b59cfd
Autor:
Zhiqiang Pang, Xinyu Mao, Shaoqun Zhou, Sheng Yu, Guizhou Liu, Chengkai Lu, Jinpeng Wan, Lingfei Hu, Peng Xu
Publikováno v:
Microbiome, Vol 11, Iss 1, Pp 1-17 (2023)
Abstract Background Plants sustain intimate relationships with diverse microbes. It is well-recognized that these plant-associated microbiota shape individual performance and fitness of host plants, but much remains to be explored regarding how they
Externí odkaz:
https://doaj.org/article/0fa3972eb1cc49cb947c86aeceece8e6
Publikováno v:
Bioresources and Bioprocessing, Vol 9, Iss 1, Pp 1-11 (2022)
Abstract The biomass pretreatment strategies using organic acids facilitate lignin removal and enhance the enzymatic digestion of cellulose. However, lignin always suffers a severe and irreversible condensation. The newly generated C–C bonds dramat
Externí odkaz:
https://doaj.org/article/b3aa498a5e8143fb8e22ec38de4bb17c
Autor:
Yubo Hu, Zhiqiang Pang
Publikováno v:
IEEE Access, Vol 10, Pp 110410-110425 (2022)
Probabilistic hesitant fuzzy sets (PHFSs), a significant expansion of hesitant fuzzy sets (HFSs), were suggested and intensively explored in order to address the problem of missing preference information. Based on previous research on PHFS, we discov
Externí odkaz:
https://doaj.org/article/4e148dbbbd0d4d81b280fb9f1ecdb6ed
Publikováno v:
PLoS ONE, Vol 18, Iss 11, p e0288639 (2023)
Unit level model is one of the classical models in small area estimation, which plays an important role with unit information data. Empirical Bayesian(EB) estimation, as the optimal estimation under normal assumption, is the most commonly used parame
Externí odkaz:
https://doaj.org/article/8898b2fe806740d9b9fa09fb12c99f95