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FIG. 3 in A synopsis of Ptisana Murdock ferns (Marattiaceae) in New Caledonia based on sequence data and morphology with the recognition of a new vulnerable species, P. soluta (Compton) Murdock & Perrie, comb. nov., stat. nov.
FIG. 3. — Ptisana soluta (Compton) Murdock & Perrie, comb. nov., stat. nov., field photos: A, frond with lamina 3-pinnate proximally and 2-pinnate distally. The frond at top-right is P. attenuata (Labill.) Murdock; B, stipes are greenish-brown at a distance; C, abaxial surface of costae and fertile lamina, showing transition from 3-pinnate to 2-pinnate; D, stipe greenish-brown and smooth; E, stipules around stipe bases. Photos: A-D, Leon Perrie from near Nouméa; E, Rémy Amice, from near Nouméa.
FIG. 1 in A synopsis of Ptisana Murdock ferns (Marattiaceae) in New Caledonia based on sequence data and morphology with the recognition of a new vulnerable species, P. soluta (Compton) Murdock & Perrie, comb. nov., stat. nov.
FIG. 1. — Ptisana attenuata (Labill.) Murdock, field photos: A, 3-pinnate frond; B, stipes are dark at a distance; C, abaxial surface of costae and lamina, with synangia; D, stipe dark and wrinkled; E, divided stipules around stipe bases. Photos: Leon Perrie, from near Nouméa.
FASTA consensus sequences obtained using amplicon-based genome sequencing of SARS-CoV-2
<p>Set of 22 FASTA consensus sequences that were produced during routine SARS-CoV-2 sequencing obtained using amplicon-based sequencing (ARTIC protocol). Those sequences were compared to those generated in NASCarD applications.</p>
pWCP alignment sequences
<p>Alignment sequences of pWCP across locations.</p>
Data from: Latent generative landscapes as maps of functional diversity in protein sequence space
<p>Variational autoencoders are unsupervised learning models with generative capabilities, when applied to protein data, they classify sequences by phylogeny and generate de novo sequences which preserve statistical properties of protein composition. While previous studies focus on clustering and generative features, here, we evaluate the underlying latent manifold in which sequence information is embedded. To investigate properties of the latent manifold, we utilize direct coupling analysis and a Potts Hamiltonian model to construct a latent generative landscape. We showcase how this landscape captures phylogenetic groupings, functional and fitness properties of several systems including Globins, β-lactamases, ion channels, and transcription factors. We provide support on how the landscape helps us understand the effects of sequence variability observed in experimental data and provides insights on directed and natural protein evolution. We propose that combining generative properties and functional predictive power of variational autoencoders and coevolutionary analysis could be beneficial in applications for protein engineering and design.</p>
Genome sequences and gene annotations for two Ophryocystis lineages
<p>Assembly, annotation, and gene sequences for the <em>Ophryocystis </em>lineages sequenced in "Genome sequence of <em>Ophryocystis elektroscirrha</em>, an apicomplexan parasite of monarch butterflies: cryptic diversity and response to host-sequestered plant chemicals." Each of the two lineages has three associated files: a genome sequence file (.fa), an annotation in .gff3 format, and gene sequences in .fna format. Sequences generated for <em>Ophryocystis elektroscirrha </em>come from direct DNA extraction and sequencing effort and are hosted elsewhere on NCBI as well. The other lineage, prefixed Ophryocystis-elektroscirrha_like, was bioinformatically extracted from the genome of an infected host. As such, we are less confident in its completeness and it is not archived elsewhere. </p>
APPENDIX 10. — Additional ITS sequences used for Appendix 9 in The Amidella clade in Europe (Basidiomycota: Amanitaceae): clarification of the contentious Amanita valens (E.-J.Gilbert) Bertault and the importance of taxon-specific PCR primers for identification
APPENDIX 10. — Additional ITS sequences used for Appendix 9, approximately in the same order. Abbreviations: MO, Mushroom Observer (https://mushroomobserver.org); iNAT, iNaturalist (https://www.inaturalist.org/observations).
Training Data for "Binning of metagenomic sequencing data" tutorial
<p><strong>Metagenomics is the study of genetic material recovered directly from environmental samples, such as soil, water, or gut contents, without the need for isolation or cultivation of individual organisms. Metagenomics binning is a process used to classify DNA sequences obtained from metagenomic sequencing into discrete groups, or bins, based on their similarity to each other</strong>. The goal of metagenomics binning is to assign the DNA sequences to the organisms or taxonomic groups that they originate from, allowing for a better understanding of the diversity and functions of the microbial communities present in the sample. This is typically achieved through computational methods that use sequence similarity, composition, and other features to group the sequences into bins.</p> <p>There are two main types of metagenomics binning: <strong>reference-based</strong> and <strong>de novo</strong>.</p> <ul> <li><strong>reference-based binning</strong> involves aligning the sequences to a database of known genomes or reference sequences</li> <li><strong>de novo binning</strong> involves clustering the sequences based on similarity without prior knowledge of the organisms or reference sequences present in the sample.</li> </ul> <p>Both methods have their strengths and limitations, and researchers often use a combination of approaches to improve the accuracy of their binning results. Metagenomics binning is an important tool for understanding the functional potential of microbial communities in various environments and has applications in fields such as biotechnology, environmental science, and human health.</p> <p>In this tutorial, we will learn how to run metagenomic binning tools and evaluate the quality of the results. In order to do that, we will use data from the study: <a href="https://www.ebi.ac.uk/metagenomics/studies/MGYS00005630#overview">Temporal shotgun metagenomic dissection of the coffee fermentation ecosystem</a> and MetaBAT2 algorithm. For an in-depth analysis of the structure and functions of the coffee microbiome, a temporal shotgun metagenomic study (six time points) was performed. The six samples have been sequenced with Illumina MiSeq utilizing whole genome sequencing.</p> <p>Based on the 6 original dataset of the coffee fermentation system, we generated mock datasets for this tutorial.</p>
DNA sequence and bioacoustic data of the Guibemantis liber complex from Madagascar (Amphibia, Mantellidae)
<p>Data from a taxonomic revision of the Guibemantis liber complex from Madagascar. The following data are included:</p> <p>- Advertisement call recordings of Guibemantis liber, G. razoky and G. razandry from different localities in wav format. See associated publication for metadata.</p> <p>- A table in Excel format with all DNA sequences used, metadata of the respective samples and specimens, and Genbank accession numbers.</p>
Figure 3 in Sexually dimorphic claws predict courtship and mating sequence in the intertidal oribatid mite Fortuynia atlantica (Acari, Oribatida)
Figure 3 Hypothetical process of courtship and sperm transfer in Fortuynia atlantica. 1) 'attraction′:
Figure 2 in Sexually dimorphic claws predict courtship and mating sequence in the intertidal oribatid mite Fortuynia atlantica (Acari, Oribatida)
Figure 2 Graphical depiction (dorsal view) of measured morphological features. (a) distance to bridge, when clasping both handles simultaneously; x - distance from line of ′handles' to the posterior end of the male, y - distance from rostrum to insertion first leg, z - length of leg I. If x+y> z no physical contact with both legs possible, if x+y
Figure 1 in Sexually dimorphic claws predict courtship and mating sequence in the intertidal oribatid mite Fortuynia atlantica (Acari, Oribatida)
Figure 1 (a) schematic drawing with landmarks and obtained measurements on first leg claw. (b-d) box-plots showing the differences in body length, claw length and claw curvature between males and females of F. atlantica. The line in the middle of each box represents the median for each group examined.
Fig. 2 in Do cytochrome c oxidase 1 gene sequences differentiate species of spirostreptid millipedes (Diplopoda: Spirostreptida: Spirostreptidae)?
Fig. 2. Saturation plot of a dataset comprising 520 nucleotides of the mitochondrial cytochrome c oxidase 1 gene created in DAMBE (Xia & Xie 2001). The GTR model was used to calculate genetic distance in substitutions per site; s – transition, v – transversion.
Fig. 1 in Do cytochrome c oxidase 1 gene sequences differentiate species of spirostreptid millipedes (Diplopoda: Spirostreptida: Spirostreptidae)?
Fig. 1. Summary of intra-specific, inter-specific and inter-generic genetic distances within representatives of the family Spirostreptidae and between members of the orders Spirostreptida, Julida and Callipodida. The dotted line represents the mean value of a category.
Fig. 3 in Do cytochrome c oxidase 1 gene sequences differentiate species of spirostreptid millipedes (Diplopoda: Spirostreptida: Spirostreptidae)?
Fig. 3. Bayesian inference tree based on an analysis of 520 nucleotides of the mitochondrial cytochrome c oxidase 1 gene showing relationships between Spirostreptida species and outgroups (Julida and Callipodida species). Numbers adjacent to taxon names are GenBank accession numbers, and indicate sequences that were downloaded from the NCBI Genbank. This tree was congruent in structure with maximum parsimony and neighbour-joining analyses of the same dataset. Nodal support values are indicated as (posterior probability / maximum parsimony bootstrap / neighbour-joining bootstrap).
Data for: Human atlastin-3 is a constitutive ER membrane fusion catalyst (phylogenetic and sequence analysis)
<p>Homotypic membrane fusion catalyzed by the atlastin (ATL) GTPase sustains the branched endoplasmic reticulum (ER) network in metazoans. Our recent discovery that two of the three human ATL paralogs (ATL1/2) are C-terminally autoinhibited implied that relief of autoinhibition would be integral to the ATL fusion mechanism. An alternative hypothesis is that the third paralog ATL3 promotes constitutive ER fusion with relief of ATL1/2 autoinhibition used conditionally. However, published studies suggest ATL3 is a weak fusogen at best. Contrary to expectations, we demonstrate here that purified human ATL3 catalyzes efficient membrane fusion in vitro and is sufficient to sustain the ER network in triple knockout cells. Strikingly, ATL3 lacks any detectable C-terminal autoinhibition, like the invertebrate <em>Drosophila</em> ATL ortholog. Phylogenetic analysis of ATL C-termini indicates that C-terminal autoinhibition is a recent evolutionary innovation. We suggest that ATL3 is a constitutive ER fusion catalyst and that ATL1/2 autoinhibition likely evolved in vertebrates as a means of upregulating ER fusion activity on demand.</p>
BLASTDB UniRef100 Virus Sequences 2023/03/01
<p>BLASTDB Version: 5<br> UniRef100 Viral Sequences 2023_03_01<br> 3,091,814 sequences; 1,162,982,857 residues; 1 volume</p>
Raw Counts: A protocol for low-input RNA-sequencing of patients with febrile neutropenia captures relevant immunological information
<p>Raw counts for scientific article: </p> <p><em>"A protocol for low-input RNA-sequencing of patients with febrile neutropenia captures relevant immunological information"</em></p> <p>Victoria Probst*<sup>1</sup>, Lotte Møller Smedegaard*<sup>2</sup>, Arman Simonyan<sup>1</sup>, Yuliu Guo<sup>1</sup>, Olga Østrup<sup>1</sup>, Kia Hee Schultz Dungu<sup>2</sup><sub>, </sub>Nadja Hawwa Vissing<sup>2</sup><sub>, </sub>Ulrikka Nygaard<sup>2</sup><sub> </sub>and<sub> </sub>Frederik Otzen Bagger<sup>1</sup></p> <p><sup>*Shared first authorship</sup></p> <p>Data description: </p> <p>The raw counts are from 88 samples of 22 patients with leukaemia and suspected infection sequenced by a low-input protocol (Takara SMART-seq HT) (96% succeeded) and 15 of these were also processed by the standard protocol (Truseq).</p> <p> </p> <p><sup>CLI.CSV: Raw counts of control samples processed using a low input RNA sequencing protocol. 15 samples processed by the low-input protocol. </sup></p> <p><sup>CRNA.CSV: Raw counts of control samples processed using a standard RNA sequencing protocol. 15 samples processed by the standard protocol. </sup></p> <p><sup>FEB.CSV: Raw gene counts from patients. 88 samples processed by the low input protocol. 4 samples failed sequencing.</sup></p> <p> </p> <p> </p> <p> </p>
Datasets for manuscript - Dirichlet diffusion score model for biological sequence generation.
<p>This repository holds the trained Dirichlet Diffusion Score models for various datasets.</p> <p><strong>best_models.tar.gz</strong></p> <p>It also contains all input data required to train your own models with scripts provided via <a href="https://github.com/jzhoulab/ddsm">github repository</a>.</p> <p><strong>data.tar.gz</strong></p> <p>This archive contains the following folders: </p> <ul> <li><strong>satnet_sudoku </strong>contains dataset with sudoku examples which we used for evaluation of sudoku model.</li> <li><strong>promoter_design</strong> contains dataset used for training promoter design model as well as Sei model weights. Please, read provided readme file before using it for training scripts. </li> </ul>
Linkage maps and genotype data of strawberry produced with skim-sequencing data
<p>The following set of files contain the results and scripts to produce those results, described in Chapter 5 of the PhD thesis of Alejandro Thérèse Navarro, entitled "How to map a million markers: linkage mapping of skim-sequencing data in strawberry". In this study, a large dataset of markers produced by whole genome resequecning of a strawberry (<em>Fragaria </em>x <em>ananassa</em>) biparental population are used to generate linkage maps. To that end the software <a href="https://github.com/Alethere/SmoothDescent">Smooth Descent</a> is used, since it is oriented to obtaining linkage maps in usin low quality (error-prone) genotype data. With this methodology we were able to produce a linkage map of 27 out of 28 chromosomes of strawberry which containing 1.85M markers in ~2400 unique genetic mpositions. We also compare this map with a linkage map produced using SNP array data and with the genome sequence assembly "Camarosa".</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.