Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Changlin, Wan"'
Autor:
Sha Cao, Wennan Chang, Changlin Wan, Xiaoyu Lu, Pengtao Dang, Xinyu Zhou, Haiqi Zhu, Jian Chen, Bo Li, Yong Zang, Yijie Wang, Chi Zhang
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 2160-2171 (2023)
The cells of colorectal cancer (CRC) in their microenvironment experience constant stress, leading to dysregulated activity in the tumor niche. As a result, cancer cells acquire alternative pathways in response to the changing microenvironment, posin
Externí odkaz:
https://doaj.org/article/52978fa5f68e434693dd8d57c27cfdc3
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 3, p e1009956 (2022)
Metastatic cancer accounts for over 90% of all cancer deaths, and evaluations of metastasis potential are vital for minimizing the metastasis-associated mortality and achieving optimal clinical decision-making. Computational assessment of metastasis
Externí odkaz:
https://doaj.org/article/39b26628dbe34ec491dda2b5fbdd9f46
Autor:
Yu Zhang, Changlin Wan, Pengcheng Wang, Wennan Chang, Yan Huo, Jian Chen, Qin Ma, Sha Cao, Chi Zhang
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S24, Pp 1-5 (2019)
Abstract Background Various statistical models have been developed to model the single cell RNA-seq expression profiles, capture its multimodality, and conduct differential gene expression test. However, for expression data generated by different exp
Externí odkaz:
https://doaj.org/article/fa5c57a58ff64adaa20df927ac574689
Autor:
Jianing Gao, Changlin Wan, Huan Zhang, Ao Li, Qiguang Zang, Rongjun Ban, Asim Ali, Zhenghua Yu, Qinghua Shi, Xiaohua Jiang, Yuanwei Zhang
Publikováno v:
BMC Bioinformatics, Vol 18, Iss 1, Pp 1-6 (2017)
Abstract Background Copy number variations (CNVs) are the main genetic structural variations in cancer genome. Detecting CNVs in genetic exome region is efficient and cost-effective in identifying cancer associated genes. Many tools had been develope
Externí odkaz:
https://doaj.org/article/b43b77d432df4d1ba2e8c2768da5b932
Autor:
Zixuan Zhang, Wennan Chang, Norah Alghamdi, Mengyuan Fei, Changlin Wan, Alex Lu, Yong Zang, Ying Xu, Wenzhuo Wu, Sha Cao, Yu Zhang, Chi Zhang
Quantitative assessment of single cell fluxome is critical for understanding the metabolic heterogeneity in diseases. Unfortunately, single cell fluxomics using laboratory approaches is currently infeasible, and none of the current flux estimation to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b6c0b11dc61b552d2bd6efb613c12d5d
https://doi.org/10.1101/2022.06.18.496660
https://doi.org/10.1101/2022.06.18.496660
Publikováno v:
The Visual Computer.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c1e2ae8e019bd2ead00177180e5cea4f
https://doi.org/10.1007/s00371-022-02474-6
https://doi.org/10.1007/s00371-022-02474-6
Autor:
Wennan Chang, Pengcheng Wang, Chi Zhang, Jian Chen, Changlin Wan, Qin Ma, Sha Cao, Yu Zhang, Yan Huo
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S24, Pp 1-5 (2019)
BMC Bioinformatics
BMC Bioinformatics
Background Various statistical models have been developed to model the single cell RNA-seq expression profiles, capture its multimodality, and conduct differential gene expression test. However, for expression data generated by different experimental
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::893c3dda5f24be5513673fe5285a3d29
https://doaj.org/article/fa5c57a58ff64adaa20df927ac574689
https://doaj.org/article/fa5c57a58ff64adaa20df927ac574689
Autor:
Melissa L. Fishel, Silpa Gampala, Norah Alghamdi, Sha Cao, Wennan Chang, Zhi Huang, Qin Ma, Jiashi Wang, Pengtao Dang, Yong Zang, Xiaoyu Lu, Changlin Wan, Chi Zhang
Publikováno v:
Genome Res
The metabolic heterogeneity and metabolic interplay between cells are known as significant contributors to disease treatment resistance. However, with the lack of a mature high-throughput single-cell metabolomics technology, we are yet to establish s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3586f55eced5c64653c36234665d25cc
https://europepmc.org/articles/PMC8494226/
https://europepmc.org/articles/PMC8494226/
Autor:
Wennan Chang, Pengdao Dang, Changlin Wan, Xiaoyu Lu, Yue Fang, Tong Zhao, Yong Zang, Bo Li, Chi Zhang, Sha Cao
In this paper, we propose a Spatial Robust Mixture Regression model to investigate the relationship between a response variable and a set of explanatory variables over the spatial domain, assuming that the relationships may exhibit complex spatially
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb2116d392cae5572d04b54f7832b90f
Publikováno v:
BIBM
Single cell RNA-sequencing (scRNA-seq) technology enables comprehensive transcriptomic profiling of thousands of cells with distinct phenotypic and physiological states in a complex tissue. Substantial efforts have been made to characterize single ce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9946abf1b7270abd5b00fc7fcb8a4eef
https://doi.org/10.1109/bibm49941.2020.9313483
https://doi.org/10.1109/bibm49941.2020.9313483