Article

JACOBI4 software for multivariate analysis of biological data

2019-11-21

Abstract excerpt

Biologists more and more have to deal with objects with non-numeric descriptions: texts (e.g. genetic sequences or even whole genomes), graphs, images, etc. There even could be no variables or descriptions at all when variability of objects is defined by similarity matrix. It is also possible to have too many variables (e.g. a magnitude of millions is reachable in mass spectrometry or genome research). In this cas...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 243ae500-4f81-5ad3-b16f-d3c2a5e2a538
DOI: 10.1101/803684

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

JACOBI4 software for multivariate analysis of biological dataDOI 10.1101/803684Read

Principal Component Analysis applied directly to Sequence Matrix.Semantic proximity Read

Principal Component Analysis applied directly to Sequence MatrixSemantic proximity Read

Principal Component Analysis Applications in COVID-19 Genome Sequence StudiesSemantic proximity Read

Principal component analysis based methods in bioinformatics studies.Semantic proximity Read

A novel definition of the multivariate coefficient of variation.Semantic proximity Read

Computational Methods and Bioinformatic ToolsSemantic proximity Read

Analysing datafied lifeSemantic proximity Read

Euclidian space and grouping of biological objects.Semantic proximity Read

Subgroup detection in genotype data using invariant coordinate selection.Semantic proximity Read

FunOrder 2.0 – a fully automated method for the identification of co-evolved genesSemantic proximity Read

Multivariate autoregressive model for a study of phylogenetic diversity.Semantic proximity Read

Stepwise iterative maximum likelihood clustering approach.Semantic proximity Read