New neuroinformatics tools will have to be developed that can interrogate the highly multi-di- mensional datasets acquired at multiple biological scales and can sufficiently capture the enormous genomic and phenomic complexity. Such tools may include supercom- puters such as Watson. Winning the $1 ...
[66] proposed an unsupervised method, denoted ‘Lisa’, for the reconstruction of cell trajectory and pseudo-time for a large number of scRNA-seq datasets. p-Creode is another unsupervised algorithm that can predict cell state-transition trajectories. Waddington-OT uses the mathematical method of ...
This article is cited by Evaluation of the role of KPNA2 mutations in breast cancer prognosis using bioinformatics datasets Layla Alnoumas Lisa van den Driest Zahra Rattray BMC Cancer (2022) Supporting data sharing Rebecca Kirk Larry Norton npj Breast Cancer (2019) In silico screening for ...
gene expression datasets (GSE36895 contained data from 29 ccRCC tissue samples and 23 tumor adjacent tissue samples; GSE53757 from 72 ccRCC samples and 72 tumor-adjacent samples; GSE66272 from 26 ccRCC samples and 26 tumor-adjacent samples) and a cohort of RCC patients in the TCGA database. ...
In this work, four TCGA datasets, BRCA, HNSC, KIRC, and THCA, were applied to our method. DriverFinder: A Gene Length-Based Network Method to Identify Cancer Driver Genes There may also be a slight change in the ratio of Democrats to Republicans on the HNSC because of the narrowed House...
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It’s easy to fool yourself: case studies on identifying bias and confounding in bio-medical datasets Preprint at: https://arxiv.org/abs/1912.07661 C.J. Kelly, et al. Key challenges for delivering clinical impact with artificial intelligenc...