Additional file 2: of Grafting or pruning in the animal tree: lateral gene transfer and gene loss?

TBLASTN search results against NR of A. pisum sequence from PFAM (J9KVH7) with homology to ASPA/ACY3 homologues. (PDF 264 kb

Additional file 4: of Grafting or pruning in the animal tree: lateral gene transfer and gene loss?

BLASTX search of A. pisum strain LSR1 unplaced genomic scaffold, Acyr_2.0 Scaffold2139 (NW_003385628.1) against NR allowing for 20,000 matches with an e-value below 0.00001. (PDF 269 kb

Additional file 3: of Grafting or pruning in the animal tree: lateral gene transfer and gene loss?

BLASTN search of A. pisum strain LSR1 unplaced genomic scaffold, Acyr_2.0 Scaffold2139 (NW_003385628.1) against NT allowing for 20,000 matches with an e-value below 0.00001. (PDF 284 kb

Burnout in the teaching staff in Primary and Nursery School at the University Hospital Motol in Prague

Schematic of the paired-end reads color scheme. An illustration of the color scheme used to describe the relationship between the insert-size for the paired-end reads (i) and the median insert-size of a participant’s library. Lighter colors indicate the read pair’s insert-size is closer to the median library insert-size. For the purpose of this illustration, these hypothetical reads have a median insert-size of 200 bp and median absolute deviation (σ) of 20 bp. (PDF 171 kb

Additional file 5: Figure S5. of Modeling the integration of bacterial rRNA fragments into the human cancer genome

RNA secondary structure of the bacterial 16S & 23S integrated rRNA gene fragments. Each colored line indicates a fragment of the Pseudomonas 16S or 23S rRNA gene that is predicted to have integrated into the human genome. The lines are color-coded based on the participant and human gene the bacterial rRNA fragment that has integrated into (C5 = CEACAM5, C6 = CEACAM6, CD = CD74, T10 = TMSB10, “_1” are upstream rRNA fragments relative to the “_2” integrations). (PDF 2295 kb

Tula

Robert Cobean, Elizabeth Jiménez y Alba Guadalupe Mastache, Tula, México, Fondo de Cultura Económica/El Colegio de México, 2012, 230 pp. 

Die klauselmäßige Einwilligung bei Bildnisrechten

Alpha diversity for all cancer types was compared pre- and post-filtering. The total number of OTUs before and after filtering for potential contaminant bacterial read pairs is plotted for each cancer type. Subsampling was done to accurately compare the large datasets, like AML and STAD to the smallest dataset, GBM. No major differences in alpha diversity were observed after filtering. (PDF 118 kb

Standardized Metadata for Human Pathogen/Vector Genomic Sequences

<div><p>High throughput sequencing has accelerated the determination of genome sequences for thousands of human infectious disease pathogens and dozens of their vectors. The scale and scope of these data are enabling genotype-phenotype association studies to identify genetic determinants of pathogen virulence and drug/insecticide resistance, and phylogenetic studies to track the origin and spread of disease outbreaks. To maximize the utility of genomic sequences for these purposes, it is essential that metadata about the pathogen/vector isolate characteristics be collected and made available in organized, clear, and consistent formats. Here we report the development of the GSCID/BRC Project and Sample Application Standard, developed by representatives of the Genome Sequencing Centers for Infectious Diseases (GSCIDs), the Bioinformatics Resource Centers (BRCs) for Infectious Diseases, and the U.S. National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health (NIH), informed by interactions with numerous collaborating scientists. It includes mapping to terms from other data standards initiatives, including the Genomic Standards Consortium’s minimal information (MIxS) and NCBI’s BioSample/BioProjects checklists and the Ontology for Biomedical Investigations (OBI). The standard includes data fields about characteristics of the organism or environmental source of the specimen, spatial-temporal information about the specimen isolation event, phenotypic characteristics of the pathogen/vector isolated, and project leadership and support. By modeling metadata fields into an ontology-based semantic framework and reusing existing ontologies and minimum information checklists, the application standard can be extended to support additional project-specific data fields and integrated with other data represented with comparable standards. The use of this metadata standard by all ongoing and future GSCID sequencing projects will provide a consistent representation of these data in the BRC resources and other repositories that leverage these data, allowing investigators to identify relevant genomic sequences and perform comparative genomics analyses that are both statistically meaningful and biologically relevant.</p></div

Core Project Attributes.

<p>*Mandatory NCBI BioProject attributes.</p

Core Sample Attributes.

<p>*Mandatory NCBI BioSample attributes in the “Pathogen: clinical or host-associated” version 1.0 package.</p