Bayesian Markov Model motif discovery tool version 2 - An expectation maximization algorithm for the de novo discovery of enriched motifs as modelled by higher-order Markov models. bioinformaticschip-seqmotif-d
compilers and specialized tools to decode encrypted data, determine the logic behind the malware algorithm and understand any hidden capabilities that the malware has not yet exhibited. Code reversing is a rare skill, and executing code reversals takes a great deal of time. For these reasons, malw...
bioinformaticssystems-biologynetwork-analysistranscriptomicsagingdifferential-expressionmutual-informationenrichment-analysistime-series-analysismicroarray-data-analysisdtw-algorithm UpdatedSep 3, 2021 HTML Load more… Improve this page Add a description, image, and links to themicroarray-data-analysistopic page so...
Microbiome-metabolome studies of the human gut have been gaining popularity in recent years, mostly due to accumulating evidence of the interplay between gut microbes, metabolites, and host health. Statistical and machine learning-based methods have been
Accurate detection of somatic structural variants (SVs) and somatic copy number aberrations (SCNAs) is critical to study the mutational processes underpinning cancer evolution. Here we describe SAVANA, an algorithm designed to detect somatic SVs and SCNA
Recent advances in single-cell technologies have enabled high-throughput molecular profiling of cells across modalities and locations. Single-cell transcriptomics data can now be complemented by chromatin accessibility, surface protein expression, adapti
Due to the continuous digitalization of our society, distributed and web-based applications become omnipresent and making them more secure gains paramount
interests along time, communication, linguistic aspect or economy. In this domain, the Dynamic Weighted Majority Concept Drift Detection (DWM-CCD) algorithm (Nosrati and Pour2011) was able to deal with sudden and gradual concept drift, but was unsuitable to tackle more complex scenarios of dataset...
(e.g., selection of background FI subtraction settings) can be made through the user interface. However, making extensive changes to the default transform script (e.g., substituting a new curve fit algorithm) requires some knowledge of the R programming language. At the same time, transform ...
For a derivation of the algorithm used to make word shift graphs while separating the frequency and sentiment information, we refer the reader to Equations 2 and 3 in [14]. We consider both the sentiment difference and frequency difference components of δhANEW(w) by writing each term of Eq...