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Autor:
Kelvin H. Lee, Madolyn L. MacDonald
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-26 (2021)
BMC Bioinformatics
BMC Bioinformatics
Background To select the most complete, continuous, and accurate assembly for an organism of interest, comprehensive quality assessment of assemblies is necessary. We present a novel tool, called Evaluation of De Novo Assemblies (EvalDNA), which uses
Autor:
Tim W. McInerney, Brian Fulton-Howard, Christopher Patterson, Devashi Paliwal, Lars S. Jermiin, Hardip R. Patel, Judy Pa, Russell H. Swerdlow, Alison Goate, Simon Easteal, Shea J. Andrews, for the Alzheimer’s Disease Neuroimaging Initiative
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-15 (2021)
BMC Bioinformatics
BMC Bioinformatics
Background Variation in mitochondrial DNA (mtDNA) identified by genotyping microarrays or by sequencing only the hypervariable regions of the genome may be insufficient to reliably assign mitochondrial genomes to phylogenetic lineages or haplogroups.
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-7 (2021)
BMC Bioinformatics
BMC Bioinformatics, BioMed Central, 2021
BMC Bioinformatics, 2021, 22, pp.449. ⟨10.1186/s12859-021-04360-9⟩
BMC Bioinformatics
BMC Bioinformatics, BioMed Central, 2021
BMC Bioinformatics, 2021, 22, pp.449. ⟨10.1186/s12859-021-04360-9⟩
Background This paper exploits recent developments in topological data analysis to present a pipeline for clustering based on Mapper, an algorithm that reduces complex data into a one-dimensional graph. Results We present a pipeline to identify and s
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-15 (2021)
BMC Bioinformatics
BMC Bioinformatics
Background A range of spatially resolved transcriptomic methods has recently emerged as a way to spatially characterize the molecular and cellular diversity of a tissue. As a consequence, an increasing number of computational techniques are developed
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-23 (2021)
BMC Bioinformatics
BMC Bioinformatics
Background Analyzing single-cell RNA sequencing (scRNAseq) data plays an important role in understanding the intrinsic and extrinsic cellular processes in biological and biomedical research. One significant effort in this area is the identification o
Autor:
Domenico Memoli, Giovanni Nassa, Giorgio Giurato, Ylenia D’Agostino, Paolo Ciaramella, Alessandro Weisz, Roberta Tarallo, Domenico Palumbo, Francesca Rizzo, Carlo Ferravante, Antonio Di Loria
Publikováno v:
BMC Bioinformatics, Vol 22, Iss S7, Pp 1-10 (2021)
BMC Bioinformatics
BMC Bioinformatics
Background Next-Generation-Sequencing (NGS) enables detection of microorganisms present in biological and other matrices of various origin and nature, allowing not only the identification of known phyla and strains but also the discovery of novel one
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-17 (2021)
BMC Bioinformatics
BMC Bioinformatics
Background The topology of metabolic networks is both well-studied and remarkably well-conserved across many species. The regulation of these networks, however, is much more poorly characterized, though it is known to be divergent across organisms—
Autor:
Thomas E. Bartlett
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-19 (2021)
BMC Bioinformatics
BMC Bioinformatics
Background Network models are well-established as very useful computational-statistical tools in cell biology. However, a genomic network model based only on gene expression data can, by definition, only infer gene co-expression networks. Hence, in o
Publikováno v:
BMC Bioinformatics, Vol 22, Iss S6, Pp 1-16 (2021)
BMC Bioinformatics
BMC Bioinformatics
Background The rapid development of single-cell RNA sequencing (scRNA-seq) enables the exploration of cell heterogeneity, which is usually done by scRNA-seq data clustering. The essence of scRNA-seq data clustering is to group cells by measuring the
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-18 (2021)
BMC Bioinformatics
BMC Bioinformatics
Background Fragment libraries play a key role in fragment-assembly based protein structure prediction, where protein fragments are assembled to form a complete three-dimensional structure. Rich and accurate structural information embedded in fragment