Package: kebabs
Type: Package
Title: Kernel-Based Analysis of Biological Sequences
Version: 1.44.0
Date: 2025-09-19
Authors@R: c(person(given = "Johannes",
                    family = "Palme",
		    role = c("aut")),
             person(given = "Ulrich",
	            family = "Bodenhofer",
		    role = c("aut", "cre", "ths"),
		    email = "ulrich@bodenhofer.com"))
Maintainer: Ulrich Bodenhofer <ulrich@bodenhofer.com>
Description: The package provides functionality for kernel-based
        analysis of DNA, RNA, and amino acid sequences via SVM-based
        methods. As core functionality, kebabs implements following
        sequence kernels: spectrum kernel, mismatch kernel, gappy pair
        kernel, and motif kernel. Apart from an efficient
        implementation of standard position-independent functionality,
        the kernels are extended in a novel way to take the position of
        patterns into account for the similarity measure. Because of
        the flexibility of the kernel formulation, other kernels like
        the weighted degree kernel or the shifted weighted degree
        kernel with constant weighting of positions are included as
        special cases. An annotation-specific variant of the kernels
        uses annotation information placed along the sequence together
        with the patterns in the sequence. The package allows for the
        generation of a kernel matrix or an explicit feature
        representation in dense or sparse format for all available
        kernels which can be used with methods implemented in other R
        packages. With focus on SVM-based methods, kebabs provides a
        framework which simplifies the usage of existing SVM
        implementations in kernlab, e1071, and LiblineaR. Binary and
        multi-class classification as well as regression tasks can be
        used in a unified way without having to deal with the different
        functions, parameters, and formats of the selected SVM. As
        support for choosing hyperparameters, the package provides
        cross validation - including grouped cross validation, grid
        search and model selection functions. For easier biological
        interpretation of the results, the package computes feature
        weights for all SVMs and prediction profiles which show the
        contribution of individual sequence positions to the prediction
        result and indicate the relevance of sequence sections for the
        learning result and the underlying biological functions.
URL: https://github.com/UBod/kebabs
License: GPL (>= 2.1)
Collate: AllClasses.R AllGenerics.R access-methods.R svmModel.R
        kebabs.R kebabsData.R runtimeMessage.R parameters.R
        sequenceKernel.R annotationSpecificKernel.R
        positionDependentKernel.R spectrum.R mismatch.R gappyPair.R
        motif.R explicitRepresentation.R coerce-methods.R
        featureWeights.R heatmap-methods.R kbsvm-methods.R
        performCrossValidation-methods.R gridSearch.R modelSelection.R
        trainsvm-methods.R predictsvm-methods.R predict-methods.R
        predictionProfile.R plot-methods.R kebabsDemo.R show-methods.R
        symmetricPair.R svm.R utils.R zzz.R
Depends: R (>= 3.3.0), Biostrings (>= 2.35.5), kernlab
Imports: methods, stats, Rcpp (>= 0.11.2), Matrix (>= 1.5-0), XVector
        (>= 0.7.3), S4Vectors (>= 0.27.3), e1071, LiblineaR, graphics,
        grDevices, utils, apcluster
LinkingTo: IRanges, XVector, Biostrings, Rcpp, S4Vectors
Suggests: SparseM, Biobase, BiocGenerics, knitr
VignetteBuilder: knitr
biocViews: SupportVectorMachine, Classification, Clustering, Regression
NeedsCompilation: yes
Config/pak/sysreqs: zlib1g-dev
Repository: https://bioc-release.r-universe.dev
Date/Publication: 2025-10-29 14:22:35 UTC
RemoteUrl: https://github.com/bioc/kebabs
RemoteRef: RELEASE_3_22
RemoteSha: db39eb7ef2a013ea9a0a118d420e1f6db0ce6762
Packaged: 2026-01-28 08:17:58 UTC; root
Author: Johannes Palme [aut],
  Ulrich Bodenhofer [aut, cre, ths]
Built: R 4.5.2; x86_64-w64-mingw32; 2026-01-28 08:20:22 UTC; windows
Archs: x64
