Parallel Algorithms for Inferring Gene Regulatory Networks: A Review.
Parallel Algorithms for Inferring Gene Regulatory Networks: A Review. Curr Genomics. 2018 Nov;19(7):603-614 Authors: Abbaszadeh O, Khanteymoori AR, Azarpeyvand A Abstract System biology problems such as whole-genome network construction from large-scale gene expression data are sophisticated and time-consuming. Therefore, using sequential algorithms are not feasible to obtain a solution in an acceptable amount of time. Today, by using massively parallel computing, it is possible to infer large-scale gene regulatory networks. Recently, establishing gene regulatory networks from large-scale datasets have drawn the noticeable attention of researchers in the field of parallel computing and system biology. In this paper, we attempt to provide a more detailed overview of the recent parallel algorithms for constructing gene regulatory networks. Firstly, fundamentals of gene regulatory networks inference and large-scale datasets challenges are given. Secondly, a detailed description of the four parallel frameworks and libraries including CUDA, OpenMP, MPI, and Hadoop is discussed. Thirdly, parallel algorithms are reviewed. Finally, some conclusions and guidelines for parallel reverse engineering are described. PMID: 30386172 [PubMed]
Authors: Horton R, Lucassen A Abstract Introduction: Clinical practice and research are traditionally seen as distinct activities that are governed by different principles and processes. Innovative technologies such as genomic testing challenge this model, involving many activities that cannot be easily categorized as purely research, or purely clinical care. Areas covered: We discuss the interdependence of research and clinical practice in the context of genomics, for example, when determining the significance of rare genetic variants, or diagnosing newly described rare diseases. We highlight the potential of the ...
CONCLUSIONS: The rate of incidental DT during decompression for LSS with and without fusion in ≥3 levels was associated with BMI and previous surgery at the same spinal level. Invasivness (SII) is valid rather for variables proper to surgery such as bledding and Op-time but no with incidence for DT and subsequent CSF-leackage. PMID: 31601067 [PubMed - as supplied by publisher]
Authors: Visocchi M, Mattogno PP Abstract PMID: 31601066 [PubMed - as supplied by publisher]
Authors: Furst T, Hoffman H, Chin LS Abstract BACKGROUND: Recent primary central nervous system lymphoma (PCNSL) literature indicates that younger patients benefit from improved survival, however, this benefit is not shared by those 70+ years of age. The purpose of this study is to examine mortality trends in PCNSL patients 70+ years of age to better understand why improved prognosis has not yet reached this rapidly growing population subset. METHODS: 2075 cases (1973-2012, age at diagnosis 70+ years) within the Surveillance, Epidemiology, and End Results (SEER) database were included in Kaplan-Meier and multiv...
Authors: Godano U Abstract PMID: 31601064 [PubMed - as supplied by publisher]