Unlabelled: Described is an algorithm to find the longest interval having at least a specified minimum bias in a sequence of characters (bases, amino acids), e.g. 'at least 0.95 (A+T)-rich'. It is based on an algorithm to find the longest interval having a non-negative sum in a sequence of positive and negative numbers. In practice, it runs in linear time; this can be guaranteed if the bias is rational.
Availability: Java code of the algorithm can be found at http://www.csse.monash.edu.au/~lloyd/tildeProgLang/Java2/Biased/.
Supplementary Information: Examples of applications to Plasmodium falciparum genomic DNA can be found at the above URL.
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http://dx.doi.org/10.1093/bioinformatics/btg135 | DOI Listing |
J Indian Soc Probab Stat
May 2024
Department of Biostatistics, School of Population Health, Virginia Commonwealth University, One Capital Square, 7th Floor, 830 East Main Street, PO Box 980032, Richmond, VA 23298-0032 USA.
Microbiome studies generate multivariate compositional responses, such as taxa counts, which are strictly non-negative, bounded, residing within a simplex, and subject to unit-sum constraint. In presence of covariates (which can be moderate to high dimensional), they are popularly modeled via the Dirichlet-Multinomial (D-M) regression framework. In this paper, we consider a Bayesian approach for estimation and inference under a D-M compositional framework, and present a comparative evaluation of some state-of-the-art continuous shrinkage priors for efficient variable selection to identify the most significant associations between available covariates, and taxonomic abundance.
View Article and Find Full Text PDFClin Genitourin Cancer
October 2024
Department of Nephrology, Houjie Hospital of Dongguan, No.21 Hetian Road, Houjie Town, Dongguan, 523000, China; Department of Nephrology, Dongguan Tungwah Hospital, Dongguan, China. Electronic address:
Background: The identification of reliable prognostic markers is crucial for optimizing patient management and improving clinical outcomes in clear cell renal cell carcinoma (ccRCC).
Methods: We used the GSE89563 dataset from the GEO database and the Kidney Clear Cell Carcinoma (KIRC) dataset from the TCGA database to develop a prognostic model based on weighted gene co-expression network analysis (WGCNA) and non-negative matrix factorization (NMF) to predict disease progression and prognosis in ccRCC.
Result: We utilized WGCNA to identify risk genes and applied NMF to stratify high-risk populations in ccRCC.
J Appl Crystallogr
June 2024
Univ. Grenoble Alpes, CNRS, Grenoble INP, Institut Néel, 38000 Grenoble, France.
J Cell Mol Med
March 2024
The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China.
Colorectal cancer (CRC) is the most prevalent malignancy of the digestive system. Glucose metabolism plays a crucial role in CRC development. However, the heterogeneity of glucose metabolic patterns in CRC is not well characterized.
View Article and Find Full Text PDFJ Comput Chem
April 2024
SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, California, USA.
Kinetic models parameterized by ab-initio calculations have led to significant improvements in understanding chemical reactions in heterogeneous catalysis. These studies have been facilitated by implementations which determine steady-state coverages and rates of mean-field micro-kinetic models. As implemented in the open-source kinetic modeling program, CatMAP, the conventional solution strategy is to use a root-finding algorithm to determine the coverage of all intermediates through the steady-state expressions, constraining all coverages to be non-negative and to properly sum to unity.
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