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Data from: Sweepstake evolution revealed by population-genetic analysis of copy-number alterations in single genomes of breast cancer
负责人:
关键词:
molecular evolution;Single-cell sequencing;Coalescent Theory;bioinformatics;Cancer genomics;Copy-number alteration
DOI:
doi:10.5061/dryad.71jp0
摘要:
. Phylogenetic tree analysis revealed genetically distinct populations, each consisting of homogeneous cells. Bioinformatics methods based on population genetics should be furt
Data from: The new bioinformatics: integrating ecological data from the gene to the biosphere
负责人:
关键词:
metadata;ecoinformatics;semantics;data integration;Data sharing;ontology;scientific workflows
DOI:
doi:10.5061/dryad.qb0d6
摘要:
Bioinformatics, the application of computational tools to the management and analysis of biological data, has stimulated rapid research advances
Data from: AftrRAD: a pipeline for accurate and efficient de novo assembly of RADseq data
负责人:
关键词:
conservation genetics;Genomics\/Proteomics;phylogeography;Bioinfomatics\/Phyloinfomatics
DOI:
doi:10.5061/dryad.sn034
摘要:
of novel bioinformatic tools that aid in the generation and analysis of these data. Here, we report the availability of AftrRAD, a bioinformatic pipeline
Data from: Whole genome sequencing of elite rice cultivars as a comprehensive information resource for marker assisted selection
负责人:
关键词:
Rice Genomic variation High throughput sequencing Copy Number Variation Marker assisted selection
DOI:
doi:10.5061/dryad.8hg32
摘要:
on or genomic selection. In this work we present sequencing and bioinformatics analyses of 104 rice varieties belonging to the major subspecies of Oryza sati
Data from: Challenges and strategies in transcriptome assembly and differential gene expression quantification. A comprehensive in silico assessment
负责人:
关键词:
Genomics\/Proteomics;Transcriptomics;molecular evolution;Bioinfomatics\/Phyloinfomatics;Ecological Genetics;Gene Structure and Function
DOI:
doi:10.5061/dryad.3t3n7
摘要:
ing), technological processing (sequencing error ?, library normalization) and bioinformatic workflow (de novo vs. mapping assembly, reference genome quality) impact
Data from: An improved hypergeometric probability method for identification of functionally linked proteins using phylogenetic profiles
负责人:
关键词:
Protein function prediction;functional similarity;phylogenetic profiles;functional annotation
DOI:
doi:10.5061/dryad.m6t4j
摘要:
Predicting functions of proteins and alternatively spliced isoforms encoded in a genome is one of the important applications of bioinformatics
Data from: ExcaliBAR: a simple and fast software utility to calculate intra- and interspecific distances from DNA barcodes
负责人:
关键词:
pairwise genetic distance;DNA Barcoding;bioinformatics;renaming haplotype
DOI:
doi:10.5061/dryad.r458n
摘要:
oming available, requiring ever more efficient bioinformatic environments and software algorithms for analysis. We here present ExcaliBAR (Extracti
Data from: Extending RAD tag analysis to microbial ecology: a comparison between multi locus sequence typing (MLST) and 2b-RAD to investi
负责人:
关键词:
Genomics\/Proteomics;Listeria monocytogenes;bacteria;Ecological Genetics;Population Genetics - Empirical
DOI:
doi:10.5061/dryad.m1bm5
摘要:
whole-genome sequencing, which also remains impractical for large population samples due to the cost of individual library preparation and bioinformatics. More traditional
Data from: Public sharing of research datasets: a pilot study of associations
负责人:
关键词:
R;Bibliometrics;Data sharing;policy evaluation;Statistical analysis;bioinformatics
DOI:
doi:10.5061/dryad.3td2f
摘要:
s will inform our ongoing larger analysis, and hopefully contribute to the development of more effective data sharing initiatives. **Earlier version present
Data from: Marker development for phylogenomics: the case of Orobanchaceae, a plant family with contrasting nutritional modes
负责人:
关键词:
bioinformatic pipeline;Target Enrichment;Solanum lycopersicum;Erythranthe guttata;Orobanchaceae;marker development;single copy nuclear genes;phylogenomics
DOI:
doi:10.5061/dryad.7b86c
摘要:
ity of reference data as well as on biological features of the study system, (semi-)automated identification of suitable markers will require specific bioinformatic

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