Zobrazeno 1 - 10
of 846
pro vyhledávání: '"Omics integration"'
Autor:
Weixuan Liu, Thao Vu, Iain R. Konigsberg, Katherine A. Pratte, Yonghua Zhuang, Katerina J. Kechris
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-23 (2024)
Abstract Summary Sparse multiple canonical correlation network analysis (SmCCNet) is a machine learning technique for integrating omics data along with a variable of interest (e.g., phenotype of complex disease), and reconstructing multi-omics networ
Externí odkaz:
https://doaj.org/article/b404423749434336831083896eed055d
Autor:
Jack Kelly, Xiaoguang Xu, James M. Eales, Bernard Keavney, Carlo Berzuini, Maciej Tomaszewski, Hui Guo
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-7 (2024)
Abstract Background Understanding the complex interactions between genes and their causal effects on diseases is crucial for developing targeted treatments and gaining insight into biological mechanisms. However, the analysis of molecular networks, e
Externí odkaz:
https://doaj.org/article/34aa23d9b61641bab4a60ab5a38c8e77
Autor:
Wen Li, Zhining Zhang, Bo Xie, Yunlin He, Kangming He, Hong Qiu, Zhiwei Lu, Chunlan Jiang, Xuanyu Pan, Yuxiao He, Wenyu Hu, Wenjian Liu, Tengcheng Que, Yanling Hu
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 659-668 (2024)
Analyzing the vast amount of omics data generated comprehensively by high-throughput sequencing technology is of utmost importance for scientists. In this context, we propose HiOmics, a cloud-based platform equipped with nearly 300 plugins designed f
Externí odkaz:
https://doaj.org/article/cc3d4f483fd84cf4ac82b8b3937ad17e
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide. Impaired insulin secretion from pancreatic beta-cells is a hallmark of T2D, but the mechanisms behind this defect are insufficiently characterized. Integrating mu
Externí odkaz:
https://doaj.org/article/c8d4693c758047b0adef87487a7425e7
Publikováno v:
Advanced Science, Vol 11, Iss 31, Pp n/a-n/a (2024)
Abstract In recent years, the integration of single‐cell multi‐omics data has provided a more comprehensive understanding of cell functions and internal regulatory mechanisms from a non‐single omics perspective, but it still suffers many challe
Externí odkaz:
https://doaj.org/article/98e6088521e44117aefc1ba90428a549
Autor:
Mengqi Wang, Naisu Yang, Mario Laterrière, David Gagné, Faith Omonijo, Eveline M. Ibeagha-Awemu
Publikováno v:
Journal of Animal Science and Biotechnology, Vol 15, Iss 1, Pp 1-21 (2024)
Abstract Background Mastitis caused by multiple factors remains one of the most common and costly disease of the dairy industry. Multi-omics approaches enable the comprehensive investigation of the complex interactions between multiple layers of info
Externí odkaz:
https://doaj.org/article/a4175590e217413db2d214922bdc66a0
Autor:
Steven Tavis, Robert L. Hettich
Publikováno v:
BMC Genomics, Vol 25, Iss 1, Pp 1-15 (2024)
Abstract In every omics experiment, genes or their products are identified for which even state of the art tools are unable to assign a function. In the biotechnology chassis organism Pseudomonas putida, these proteins of unknown function make up 14%
Externí odkaz:
https://doaj.org/article/d606eb770ec5438dad8e3fb21607c319
Publikováno v:
Applied Biological Chemistry, Vol 67, Iss 1, Pp 1-18 (2024)
Abstract Soybeans are a significant agricultural product in China, with certain geographical locations often yielding higher quality, and thus more expensive, soybean crops. In this study, metabolomics and transcriptomics analyses were conducted on s
Externí odkaz:
https://doaj.org/article/c3d141505e2c470e8e341aa80156f402
Publikováno v:
BioData Mining, Vol 17, Iss 1, Pp 1-19 (2024)
Abstract Background Integrating multi-omics data is emerging as a critical approach in enhancing our understanding of complex diseases. Innovative computational methods capable of managing high-dimensional and heterogeneous datasets are required to u
Externí odkaz:
https://doaj.org/article/2a427d2549954e729700f05a8dd602a4
Autor:
Bingjun Li, Sheida Nabavi
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-19 (2024)
Abstract Background The recent development of high-throughput sequencing has created a large collection of multi-omics data, which enables researchers to better investigate cancer molecular profiles and cancer taxonomy based on molecular subtypes. In
Externí odkaz:
https://doaj.org/article/98d14d666f8243a6bfde9a2f2e7fbf48