R-universe search: biologicalquestion

bioc

projectR:Functions for the projection of weights from PCA, CoGAPS, NMF, correlation, and clustering

Functions for the projection of data into the spaces defined by PCA, CoGAPS, NMF, correlation, and clustering.

Maintained by Genevieve Stein-OBrien. Last updated 5 months ago.

functionalprediction generegulation biologicalquestion software

10.0 match 62 stars 8.11 score 70 scripts

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musicatk:Mutational Signature Comprehensive Analysis Toolkit

Mutational signatures are carcinogenic exposures or aberrant cellular processes that can cause alterations to the genome. We created musicatk (MUtational SIgnature Comprehensive Analysis ToolKit) to address shortcomings in versatility and ease of use in other pre-existing computational tools. Although many different types of mutational data have been generated, current software packages do not have a flexible framework to allow users to mix and match different types of mutations in the mutational signature inference process. Musicatk enables users to count and combine multiple mutation types, including SBS, DBS, and indels. Musicatk calculates replication strand, transcription strand and combinations of these features along with discovery from unique and proprietary genomic feature associated with any mutation type. Musicatk also implements several methods for discovery of new signatures as well as methods to infer exposure given an existing set of signatures. Musicatk provides functions for visualization and downstream exploratory analysis including the ability to compare signatures between cohorts and find matching signatures in COSMIC V2 or COSMIC V3.

Maintained by Joshua D. Campbell. Last updated 5 months ago.

software biologicalquestion somaticmutation variantannotation

10.0 match 13 stars 7.02 score 20 scripts

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tricycle:tricycle: Transferable Representation and Inference of cell cycle

The package contains functions to infer and visualize cell cycle process using Single Cell RNASeq data. It exploits the idea of transfer learning, projecting new data to the previous learned biologically interpretable space. We provide a pre-learned cell cycle space, which could be used to infer cell cycle time of human and mouse single cell samples. In addition, we also offer functions to visualize cell cycle time on different embeddings and functions to build new reference.

Maintained by Shijie Zheng. Last updated 5 months ago.

singlecell software transcriptomics rnaseq transcription biologicalquestion dimensionreduction immunooncology

10.0 match 24 stars 6.52 score 46 scripts

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methylclock:Methylclock - DNA methylation-based clocks

This package allows to estimate chronological and gestational DNA methylation (DNAm) age as well as biological age using different methylation clocks. Chronological DNAm age (in years) : Horvath's clock, Hannum's clock, BNN, Horvath's skin+blood clock, PedBE clock and Wu's clock. Gestational DNAm age : Knight's clock, Bohlin's clock, Mayne's clock and Lee's clocks. Biological DNAm clocks : Levine's clock and Telomere Length's clock.

Maintained by Dolors Pelegri-Siso. Last updated 5 months ago.

dnamethylation biologicalquestion preprocessing statisticalmethod normalization cpp

10.0 match 39 stars 6.52 score 28 scripts

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CatsCradle:This package provides methods for analysing spatial transcriptomics data and for discovering gene clusters

This package addresses two broad areas. It allows for in-depth analysis of spatial transcriptomic data by identifying tissue neighbourhoods. These are contiguous regions of tissue surrounding individual cells. 'CatsCradle' allows for the categorisation of neighbourhoods by the cell types contained in them and the genes expressed in them. In particular, it produces Seurat objects whose individual elements are neighbourhoods rather than cells. In addition, it enables the categorisation and annotation of genes by producing Seurat objects whose elements are genes.

Maintained by Michael Shapiro. Last updated 1 months ago.

biologicalquestion statisticalmethod geneexpression singlecell transcriptomics spatial

10.0 match 3 stars 6.50 score

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YAPSA:Yet Another Package for Signature Analysis

This package provides functions and routines for supervised analyses of mutational signatures (i.e., the signatures have to be known, cf. L. Alexandrov et al., Nature 2013 and L. Alexandrov et al., Bioaxiv 2018). In particular, the family of functions LCD (LCD = linear combination decomposition) can use optimal signature-specific cutoffs which takes care of different detectability of the different signatures. Moreover, the package provides different sets of mutational signatures, including the COSMIC and PCAWG SNV signatures and the PCAWG Indel signatures; the latter infering that with YAPSA, the concept of supervised analysis of mutational signatures is extended to Indel signatures. YAPSA also provides confidence intervals as computed by profile likelihoods and can perform signature analysis on a stratified mutational catalogue (SMC = stratify mutational catalogue) in order to analyze enrichment and depletion patterns for the signatures in different strata.

Maintained by Zuguang Gu. Last updated 5 months ago.

sequencing dnaseq somaticmutation visualization clustering genomicvariation statisticalmethod biologicalquestion

10.0 match 6.41 score 57 scripts

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OncoSimulR:Forward Genetic Simulation of Cancer Progression with Epistasis

Functions for forward population genetic simulation in asexual populations, with special focus on cancer progression. Fitness can be an arbitrary function of genetic interactions between multiple genes or modules of genes, including epistasis, order restrictions in mutation accumulation, and order effects. Fitness (including just birth, just death, or both birth and death) can also be a function of the relative and absolute frequencies of other genotypes (i.e., frequency-dependent fitness). Mutation rates can differ between genes, and we can include mutator/antimutator genes (to model mutator phenotypes). Simulating multi-species scenarios and therapeutic interventions, including adaptive therapy, is also possible. Simulations use continuous-time models and can include driver and passenger genes and modules. Also included are functions for: simulating random DAGs of the type found in Oncogenetic Trees, Conjunctive Bayesian Networks, and other cancer progression models; plotting and sampling from single or multiple realizations of the simulations, including single-cell sampling; plotting the parent-child relationships of the clones; generating random fitness landscapes (Rough Mount Fuji, House of Cards, additive, NK, Ising, and Eggbox models) and plotting them.

Maintained by Ramon Diaz-Uriarte. Last updated 11 days ago.

biologicalquestion somaticmutation cpp

10.0 match 7 stars 6.06 score 68 scripts

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discordant:The Discordant Method: A Novel Approach for Differential Correlation

Discordant is an R package that identifies pairs of features that correlate differently between phenotypic groups, with application to -omics data sets. Discordant uses a mixture model that “bins” molecular feature pairs based on their type of coexpression or coabbundance. Algorithm is explained further in "Differential Correlation for Sequencing Data"" (Siska et al. 2016).

Maintained by McGrath Max. Last updated 5 months ago.

immunooncology biologicalquestion statisticalmethod mrnamicroarray microarray genetics rnaseq cpp

10.0 match 10 stars 6.05 score 14 scripts

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INDEED:Interactive Visualization of Integrated Differential Expression and Differential Network Analysis for Biomarker Candidate Selection Package

An R package for integrated differential expression and differential network analysis based on omic data for cancer biomarker discovery. Both correlation and partial correlation can be used to generate differential network to aid the traditional differential expression analysis to identify changes between biomolecules on both their expression and pairwise association levels. A detailed description of the methodology has been published in Methods journal (PMID: 27592383). An interactive visualization feature allows for the exploration and selection of candidate biomarkers.

Maintained by Ressom group. Last updated 5 months ago.

immunooncology software researchfield biologicalquestion statisticalmethod differentialexpression massspectrometry metabolomics

10.0 match 4 stars 5.92 score 10 scripts

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MetID:Network-based prioritization of putative metabolite IDs

This package uses an innovative network-based approach that will enhance our ability to determine the identities of significant ions detected by LC-MS.

Maintained by Zhenzhi Li. Last updated 5 months ago.

assaydomain biologicalquestion infrastructure researchfield statisticalmethod technology workflowstep network kegg

10.0 match 1 stars 5.74 score 110 scripts

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rexposome:Exposome exploration and outcome data analysis

Package that allows to explore the exposome and to perform association analyses between exposures and health outcomes.

Maintained by Xavier Escribà Montagut. Last updated 5 months ago.

software biologicalquestion infrastructure dataimport datarepresentation biomedicalinformatics experimentaldesign multiplecomparison classification clustering

10.0 match 5.70 score 28 scripts 1 dependents

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CoSIA:An Investigation Across Different Species and Tissues

Cross-Species Investigation and Analysis (CoSIA) is a package that provides researchers with an alternative methodology for comparing across species and tissues using normal wild-type RNA-Seq Gene Expression data from Bgee. Using RNA-Seq Gene Expression data, CoSIA provides multiple visualization tools to explore the transcriptome diversity and variation across genes, tissues, and species. CoSIA uses the Coefficient of Variation and Shannon Entropy and Specificity to calculate transcriptome diversity and variation. CoSIA also provides additional conversion tools and utilities to provide a streamlined methodology for cross-species comparison.

Maintained by Amanda D. Clark. Last updated 5 months ago.

software biologicalquestion geneexpression multiplecomparison thirdpartyclient dataimport gui

10.0 match 5 stars 5.70 score 3 scripts

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VplotR:Set of tools to make V-plots and compute footprint profiles

The pattern of digestion and protection from DNA nucleases such as DNAse I, micrococcal nuclease, and Tn5 transposase can be used to infer the location of associated proteins. This package contains useful functions to analyze patterns of paired-end sequencing fragment density. VplotR facilitates the generation of V-plots and footprint profiles over single or aggregated genomic loci of interest.

Maintained by Jacques Serizay. Last updated 5 months ago.

nucleosomepositioning coverage sequencing biologicalquestion atacseq alignment

10.0 match 10 stars 5.64 score 11 scripts

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similaRpeak:Metrics to estimate a level of similarity between two ChIP-Seq profiles

This package calculates metrics which quantify the level of similarity between ChIP-Seq profiles. More specifically, the package implements six pseudometrics specialized in pattern similarity detection in ChIP-Seq profiles.

Maintained by Astrid Deschênes. Last updated 5 months ago.

biologicalquestion chipseq genetics multiplecomparison differentialexpression bioconductor bioconductor-package chip-profiles chip-seq metrics

10.0 match 7 stars 5.62 score 7 scripts

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enrichViewNet:From functional enrichment results to biological networks

This package enables the visualization of functional enrichment results as network graphs. First the package enables the visualization of enrichment results, in a format corresponding to the one generated by gprofiler2, as a customizable Cytoscape network. In those networks, both gene datasets (GO terms/pathways/protein complexes) and genes associated to the datasets are represented as nodes. While the edges connect each gene to its dataset(s). The package also provides the option to create enrichment maps from functional enrichment results. Enrichment maps enable the visualization of enriched terms into a network with edges connecting overlapping genes.

Maintained by Astrid Deschênes. Last updated 5 months ago.

biologicalquestion software network networkenrichment go cystocape functional-enrichment

10.0 match 5 stars 5.54 score 6 scripts

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consensusSeekeR:Detection of consensus regions inside a group of experiences using genomic positions and genomic ranges

This package compares genomic positions and genomic ranges from multiple experiments to extract common regions. The size of the analyzed region is adjustable as well as the number of experiences in which a feature must be present in a potential region to tag this region as a consensus region. In genomic analysis where feature identification generates a position value surrounded by a genomic range, such as ChIP-Seq peaks and nucleosome positions, the replication of an experiment may result in slight differences between predicted values. This package enables the conciliation of the results into consensus regions.

Maintained by Astrid Deschênes. Last updated 5 months ago.

biologicalquestion chipseq genetics multiplecomparison transcription peakdetection sequencing coverage chip-seq-analysis genomic-data-analysis nucleosome-positioning

10.0 match 1 stars 5.26 score 5 scripts 1 dependents

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qsvaR:Generate Quality Surrogate Variable Analysis for Degradation Correction

The qsvaR package contains functions for removing the effect of degration in rna-seq data from postmortem brain tissue. The package is equipped to help users generate principal components associated with degradation. The components can be used in differential expression analysis to remove the effects of degradation.

Maintained by Hedia Tnani. Last updated 3 months ago.

software workflowstep normalization biologicalquestion differentialexpression sequencing coverage bioconductor brain degradation human qsva

10.0 match 5.26 score 4 scripts

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CNVMetrics:Copy Number Variant Metrics

The CNVMetrics package calculates similarity metrics to facilitate copy number variant comparison among samples and/or methods. Similarity metrics can be employed to compare CNV profiles of genetically unrelated samples as well as those with a common genetic background. Some metrics are based on the shared amplified/deleted regions while other metrics rely on the level of amplification/deletion. The data type used as input is a plain text file containing the genomic position of the copy number variations, as well as the status and/or the log2 ratio values. Finally, a visualization tool is provided to explore resulting metrics.

Maintained by Astrid Deschênes. Last updated 5 months ago.

biologicalquestion software copynumbervariation cnv copy-number-variation metrics r-language

10.0 match 4 stars 5.08 score 8 scripts

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decompTumor2Sig:Decomposition of individual tumors into mutational signatures by signature refitting

Uses quadratic programming for signature refitting, i.e., to decompose the mutation catalog from an individual tumor sample into a set of given mutational signatures (either Alexandrov-model signatures or Shiraishi-model signatures), computing weights that reflect the contributions of the signatures to the mutation load of the tumor.

Maintained by Rosario M. Piro. Last updated 5 months ago.

software snp sequencing dnaseq genomicvariation somaticmutation biomedicalinformatics genetics biologicalquestion statisticalmethod

10.0 match 1 stars 4.78 score 10 scripts 1 dependents

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TrajectoryGeometry:This Package Discovers Directionality in Time and Pseudo-times Series of Gene Expression Patterns

Given a time series or pseudo-times series of gene expression data, we might wish to know: Do the changes in gene expression in these data exhibit directionality? Are there turning points in this directionality. Do different subsets of the data move in different directions? This package uses spherical geometry to probe these sorts of questions. In particular, if we are looking at (say) the first n dimensions of the PCA of gene expression, directionality can be detected as the clustering of points on the (n-1)-dimensional sphere.

Maintained by Michael Shapiro. Last updated 5 months ago.

biologicalquestion statisticalmethod geneexpression singlecell

10.0 match 4.60 score 7 scripts

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NoRCE:NoRCE: Noncoding RNA Sets Cis Annotation and Enrichment

While some non-coding RNAs (ncRNAs) are assigned critical regulatory roles, most remain functionally uncharacterized. This presents a challenge whenever an interesting set of ncRNAs needs to be analyzed in a functional context. Transcripts located close-by on the genome are often regulated together. This genomic proximity on the sequence can hint to a functional association. We present a tool, NoRCE, that performs cis enrichment analysis for a given set of ncRNAs. Enrichment is carried out using the functional annotations of the coding genes located proximal to the input ncRNAs. Other biologically relevant information such as topologically associating domain (TAD) boundaries, co-expression patterns, and miRNA target prediction information can be incorporated to conduct a richer enrichment analysis. To this end, NoRCE includes several relevant datasets as part of its data repository, including cell-line specific TAD boundaries, functional gene sets, and expression data for coding & ncRNAs specific to cancer. Additionally, the users can utilize custom data files in their investigation. Enrichment results can be retrieved in a tabular format or visualized in several different ways. NoRCE is currently available for the following species: human, mouse, rat, zebrafish, fruit fly, worm, and yeast.

Maintained by Gulden Olgun. Last updated 5 months ago.

biologicalquestion differentialexpression genomeannotation genesetenrichment genetarget genomeassembly go

10.0 match 1 stars 4.60 score 6 scripts

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methInheritSim:Simulating Whole-Genome Inherited Bisulphite Sequencing Data

Simulate a multigeneration methylation case versus control experiment with inheritance relation using a real control dataset.

Maintained by Pascal Belleau. Last updated 5 months ago.

biologicalquestion epigenetics dnamethylation differentialmethylation methylseq software immunooncology statisticalmethod wholegenome sequencing bisulphite-sequencing inheritance methylation simulation

10.0 match 1 stars 4.60 score 1 scripts

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OGRE:Calculate, visualize and analyse overlap between genomic regions

OGRE calculates overlap between user defined genomic region datasets. Any regions can be supplied i.e. genes, SNPs, or reads from sequencing experiments. Key numbers help analyse the extend of overlaps which can also be visualized at a genomic level.

Maintained by Sven Berres. Last updated 5 months ago.

software workflowstep biologicalquestion annotation metagenomics visualization sequencing

10.0 match 2 stars 4.60 score 4 scripts

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methylInheritance:Permutation-Based Analysis associating Conserved Differentially Methylated Elements Across Multiple Generations to a Treatment Effect

Permutation analysis, based on Monte Carlo sampling, for testing the hypothesis that the number of conserved differentially methylated elements, between several generations, is associated to an effect inherited from a treatment and that stochastic effect can be dismissed.

Maintained by Astrid Deschênes. Last updated 5 months ago.

biologicalquestion epigenetics dnamethylation differentialmethylation methylseq software immunooncology statisticalmethod wholegenome sequencing analysis bioconductor bioinformatics cpg differentially-methylated-elements inheritance monte-carlo-sampling permutation

10.0 match 4.60 score 1 scripts

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ChIPanalyser:ChIPanalyser: Predicting Transcription Factor Binding Sites

ChIPanalyser is a package to predict and understand TF binding by utilizing a statistical thermodynamic model. The model incorporates 4 main factors thought to drive TF binding: Chromatin State, Binding energy, Number of bound molecules and a scaling factor modulating TF binding affinity. Taken together, ChIPanalyser produces ChIP-like profiles that closely mimic the patterns seens in real ChIP-seq data.

Maintained by Patrick C.N. Martin. Last updated 5 months ago.

software biologicalquestion workflowstep transcription sequencing chiponchip coverage alignment chipseq sequencematching dataimport peakdetection

10.0 match 4.38 score 12 scripts

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CIMICE:CIMICE-R: (Markov) Chain Method to Inferr Cancer Evolution

CIMICE is a tool in the field of tumor phylogenetics and its goal is to build a Markov Chain (called Cancer Progression Markov Chain, CPMC) in order to model tumor subtypes evolution. The input of CIMICE is a Mutational Matrix, so a boolean matrix representing altered genes in a collection of samples. These samples are assumed to be obtained with single-cell DNA analysis techniques and the tool is specifically written to use the peculiarities of this data for the CMPC construction.

Maintained by Nicolò Rossi. Last updated 5 months ago.

software biologicalquestion networkinference researchfield phylogenetics statisticalmethod graphandnetwork technology singlecell

10.0 match 4.30 score 5 scripts

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RJMCMCNucleosomes:Bayesian hierarchical model for genome-wide nucleosome positioning with high-throughput short-read data (MNase-Seq)

This package does nucleosome positioning using informative Multinomial-Dirichlet prior in a t-mixture with reversible jump estimation of nucleosome positions for genome-wide profiling.

Maintained by Astrid Deschênes. Last updated 5 months ago.

biologicalquestion chipseq nucleosomepositioning software statisticalmethod bayesian sequencing coverage bayesian-t-mixture bioconductor c-plus-plus genome-wide-profiling multinomial-dirichlet-prior nucleosome-positioning nucleosomes reversible-jump-mcmc gsl cpp

10.0 match 4.30 score 1 scripts

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epimutacions:Robust outlier identification for DNA methylation data

The package includes some statistical outlier detection methods for epimutations detection in DNA methylation data. The methods included in the package are MANOVA, Multivariate linear models, isolation forest, robust mahalanobis distance, quantile and beta. The methods compare a case sample with a suspected disease against a reference panel (composed of healthy individuals) to identify epimutations in the given case sample. It also contains functions to annotate and visualize the identified epimutations.

Maintained by Dolors Pelegri-Siso. Last updated 5 months ago.

dnamethylation biologicalquestion preprocessing statisticalmethod normalization cpp

10.0 match 4.23 score 28 scripts

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pram:Pooling RNA-seq datasets for assembling transcript models

Publicly available RNA-seq data is routinely used for retrospective analysis to elucidate new biology. Novel transcript discovery enabled by large collections of RNA-seq datasets has emerged as one of such analysis. To increase the power of transcript discovery from large collections of RNA-seq datasets, we developed a new R package named Pooling RNA-seq and Assembling Models (PRAM), which builds transcript models in intergenic regions from pooled RNA-seq datasets. This package includes functions for defining intergenic regions, extracting and pooling related RNA-seq alignments, predicting, selected, and evaluating transcript models.

Maintained by Peng Liu. Last updated 5 months ago.

software technology sequencing rnaseq biologicalquestion geneprediction genomeannotation researchfield transcriptomics bioconductor-package genome-annotation rna-seq transcript-model

10.0 match 1 stars 4.18 score 3 scripts

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OMICsPCA:An R package for quantitative integration and analysis of multiple omics assays from heterogeneous samples

OMICsPCA is an analysis pipeline designed to integrate multi OMICs experiments done on various subjects (e.g. Cell lines, individuals), treatments (e.g. disease/control) or time points and to analyse such integrated data from various various angles and perspectives. In it's core OMICsPCA uses Principal Component Analysis (PCA) to integrate multiomics experiments from various sources and thus has ability to over data insufficiency issues by using the ingegrated data as representatives. OMICsPCA can be used in various application including analysis of overall distribution of OMICs assays across various samples /individuals /time points; grouping assays by user-defined conditions; identification of source of variation, similarity/dissimilarity between assays, variables or individuals.

Maintained by Subhadeep Das. Last updated 5 months ago.

immunooncology multiplecomparison principalcomponent datarepresentation workflow visualization dimensionreduction clustering biologicalquestion epigeneticsworkflow transcription geneticvariability gui biomedicalinformatics epigenetics functionalgenomics singlecell

10.0 match 4.00 score 1 scripts

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GSALightning:Fast Permutation-based Gene Set Analysis

GSALightning provides a fast implementation of permutation-based gene set analysis for two-sample problem. This package is particularly useful when testing simultaneously a large number of gene sets, or when a large number of permutations is necessary for more accurate p-values estimation.

Maintained by Billy Heung Wing Chang. Last updated 5 months ago.

software biologicalquestion genesetenrichment differentialexpression geneexpression transcription

10.0 match 5 stars 4.00 score 4 scripts

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TFARM:Transcription Factors Association Rules Miner

It searches for relevant associations of transcription factors with a transcription factor target, in specific genomic regions. It also allows to evaluate the Importance Index distribution of transcription factors (and combinations of transcription factors) in association rules.

Maintained by Liuba Nausicaa Martino. Last updated 5 months ago.

biologicalquestion infrastructure statisticalmethod transcription

10.0 match 4.00 score 2 scripts

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TFHAZ:Transcription Factor High Accumulation Zones

It finds trascription factor (TF) high accumulation DNA zones, i.e., regions along the genome where there is a high presence of different transcription factors. Starting from a dataset containing the genomic positions of TF binding regions, for each base of the selected chromosome the accumulation of TFs is computed. Three different types of accumulation (TF, region and base accumulation) are available, together with the possibility of considering, in the single base accumulation computing, the TFs present not only in that single base, but also in its neighborhood, within a window of a given width. Two different methods for the search of TF high accumulation DNA zones, called "binding regions" and "overlaps", are available. In addition, some functions are provided in order to analyze, visualize and compare results obtained with different input parameters.

Maintained by Gaia Ceddia. Last updated 5 months ago.

software biologicalquestion transcription chipseq coverage

10.0 match 4.00 score 2 scripts

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deltaCaptureC:This Package Discovers Meso-scale Chromatin Remodeling from 3C Data

This package discovers meso-scale chromatin remodelling from 3C data. 3C data is local in nature. It givens interaction counts between restriction enzyme digestion fragments and a preferred 'viewpoint' region. By binning this data and using permutation testing, this package can test whether there are statistically significant changes in the interaction counts between the data from two cell types or two treatments.

Maintained by Michael Shapiro. Last updated 5 months ago.

biologicalquestion statisticalmethod

10.0 match 3.48 score 1 scripts

fabriciomlopes

BASiNETEntropy:Classification of RNA Sequences using Complex Network and Information Theory

It makes the creation of networks from sequences of RNA, with this is done the abstraction of characteristics of these networks with a methodology of maximum entropy for the purpose of making a classification between the classes of the sequences. There are two data present in the 'BASiNET' package, "mRNA", and "ncRNA" with 10 sequences. These sequences were taken from the data set used in the article (LI, Aimin; ZHANG, Junying; ZHOU, Zhongyin, 2014) <doi:10.1186/1471-2105-15-311>, these sequences are used to run examples.

Maintained by Fabricio Martins Lopes. Last updated 2 years ago.

software biologicalquestion geneprediction functionalprediction network classification

10.0 match 2.70 score 6 scripts

fabriciomlopes

BASiNET:Classification of RNA Sequences using Complex Network Theory

It makes the creation of networks from sequences of RNA, with this is done the abstraction of characteristics of these networks with a methodology of threshold for the purpose of making a classification between the classes of the sequences. There are four data present in the 'BASiNET' package, "sequences", "sequences2", "sequences-predict" and "sequences2-predict" with 11, 10, 11 and 11 sequences respectively. These sequences were taken from the data set used in the article (LI, Aimin; ZHANG, Junying; ZHOU, Zhongyin, 2014) <doi:10.1186/1471-2105-15-311>, these sequences are used to run examples. The BASiNET was published on Nucleic Acids Research, (ITO, Eric; KATAHIRA, Isaque; VICENTE, Fábio; PEREIRA, Felipe; LOPES, Fabrício, 2018) <doi:10.1093/nar/gky462>.

Maintained by Fabricio Martins Lopes. Last updated 3 years ago.

software biologicalquestion geneprediction openjdk

10.0 match 2.48 score 7 scripts