Results for "Probabilistic"
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A probabilistic framework for structural variant discovery. Ryan M Layer, Colby Chiang, Aaron R Quinlan, and Ira M Hall. 2014. "LUMPY: a Probabilistic Framework for Structural Vari...2825 days ago
- ...d analyses. The MEME Suite supports motif-based analysis of DNA, RNA and protein sequences. It provides motif discovery algorithms using both probabilistic (MEME) and discrete models (M...
2705 days ago
- ...idual organisms and their interactions. Here we developed an automated metagenome binning software, called MetaBAT, which integrates empirical probabilistic distances of genome abundance...
2632 days ago
FSA: Fast Statistical Alignment
FSA is a probabilistic multiple sequence alignment algorithm which uses a "distance-based" approach to aligning homologous protein, RNA or DNA sequences. Much as distance-based...2660 days ago
ConPADE: Genome Assembly Ploidy Estimation from Next-Generation Sequencing Data
ConPADE (Contig Ploidy and Allele Dosage Estimation), a probabilistic method that estimates the ploidy of any given contig/scaffold based on its allele proportions. In the process, they...2642 days ago
SEX-DETector: A Probabilistic Approach to Study Sex Chromosomes in Non-Model Organisms
SEX-DETector is a probabilistic method that relies on RNAseq data from a cross (parents and progeny of each sex) to infer autosomal and sex-linked genes (genes located on the non r...2182 days ago
CSBFinder: Discovery of colinear syntenic blocks across thousands of prokaryotic genomes
...a. CSBFinder incorporates an efficient algorithm that identifies CSBs in large genomic datasets. The discovered CSBs are ranked according to a probabilistic score and clustered to famili...2035 days ago
kallisto: a program for quantifying abundances of transcripts from bulk and single-cell RNA-Seq data
...tools. kallisto is described in detail in: Nicolas L Bray, Harold Pimentel, Páll Melsted and Lior Pachter, Near-optimal probabilistic RNA-seq quantification, Natur...1960 days ago
Machine learning training and courses in bioinformatics !
...g randomness and uncertainty of data noise and in generalization. In this class, we will learn basics about probabilistic models and machine learning techniques. We will focus on probabilistic models (Markov models, Hidden...1602 days ago
