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DATASET: De novo assembly and functional annotation of the heart + hemolymph transcriptome in the Caribbean spiny lobster Panulirus argus
<p>The spiny lobster <em>Panulirus argus</em> is an ecologically relevant species in shallow water coral reefs and target of the most lucrative fishery in the greater Caribbean region. This study reports, for the first time, the heart + hemolymph transcriptome of the Caribbean spiny lobster<em> Panulirus argus</em> assembled from short Illumina 150 bp PE raw reads. A total 80,152,094 raw reads were assembled using the Oyster River Protocol pipeline that aspires to become the standard protocol for <em>de novo</em> transcriptome assembly. The assembly resulted in a total of 254,773 transcripts. Functional gene annotation was conducted using the software package 'dammit' that also aspires to become the standard protocol for <em>de novo</em> transcriptome annotation. Lastly, gene enrichment analyses were conducted using the Gene Ontology (GO), KEGG pathway analyses (Kaas), and KOG (WebMGA) databases. This resource will be of utmost importance in future research aiming at exploring the effect of local and regional anthropogenic disturbances as well as global climate change on the molecular physiology of this overexploited species.</p>
Molecular datasets from "SMILES-Based Deep Generative Scaffold Decorator for De-Novo Drug Design"
<p>Herein find the molecular datasets from "<a href="https://chemrxiv.org/articles/SMILES-Based_Deep_Generative_Scaffold_Decorator_for_De-Novo_Drug_Design/11638383">SMILES-Based Deep Generative Scaffold Decorator for De-Novo Drug Design</a>". These were generated with SMILES-based scaffold decorator generative models trained with two training sets (DRD2 and ChEMBL). These generative models require a partially-built molecule (scaffold) as input and output several possible completions for each scaffold. Each dataset corresponds to a model trained with the ChEMBL or DRD2 sets, wither multi-step (ms) or single-step (ss) and the provenance of the scaffolds (validation set, or non-dataset).</p> <p>The molecules generated are annotated with a set of descriptors. The DRD2 datasets have the predicted probability of each molecule to be active on DRD2 (p) obtained from a Random Forest model. The ChEMBL model's descriptors are related to the synthesizability of the molecules (see manuscript). Also, the datasets decorated from validation set scaffolds are annotated whether they are part of the validation set (in_validation).</p>
Introduction to Ancient Metagenomics Textbook (Edition 2025): de novo Genome Assembly
<p>Data and conda software environment file for the chapter '<em>de novo</em> Genome Assembly' of the SPAAM Community's textbook: Introduction to Ancient Metagenomics (https://www.spaam-community.org/intro-to-ancient-metagenomics-book).</p>
Ramonda serbica de novo transcriptome database
<p>Ramonda serbica de novo transcriptome database translated into amino acid seq. Hydrated and desiccated leaf tissue</p>
Data From: The Oyster River Protocol: A multi assembler and kmer approach for de novo transcriptome assembly.
<p>Characterizing transcriptomes in non-model organisms has resulted in a massive increase in our understanding of biological phenomena. This boon, largely made possible via high-throughput sequencing, means that studies of functional, evolutionary and population genomics are now being done by hundreds or even thousands of labs around the world. For many, these studies begin with a <em>de novo</em> transcriptome assembly, which is a technically complicated process involving several discrete steps. The Oyster River Protocol (ORP), described here, implements a standardized and benchmarked set of bioinformatic processes, resulting in an assembly with enhanced qualities over other standard assembly methods. Specifically, ORP produced assemblies have higher Detonate and TransRate scores and mapping rates, which is largely a product of the fact that it leverages a multi-assembler and kmer assembly process, thereby bypassing the shortcomings of any one approach. These improvements are important, as previously unassembled transcripts are included in ORP assemblies, resulting in a significant enhancement of the power of downstream analysis. Further, as part of this study, I show that assembly quality is unrelated with the number of reads generated, above 30 million reads. Code Availability: The version controlled open-source code is available at <a href="https://github.com/macmanes-lab/Oyster_River_Protocol">https://github.com/macmanes-lab/Oyster_River_Protocol</a>. Instructions for software installation and use, and other details are available at <a href="http://oyster-river-protocol.rtfd.org/">http://oyster-river-protocol.rtfd.org/</a>.</p>
Aversive imagery causes de novo fear conditioning (Open Data and Open Materials)
<p><strong>Open Data and Open Materials of: Mueller, E. M., Sperl, M. F. J., & Panitz, C. (2019). Aversive imagery causes de novo fear conditioning. <em>Psychological Science</em>, <em>30</em>(7), 1001–1015.</strong></p> <p>In classical fear conditioning, neutral conditioned stimuli (CS) that have been paired with aversive physical unconditioned stimuli eventually trigger fear responses. Here, we test whether aversive mental images systematically paired with a CS may also cause de novo fear learning in the absence of any external aversive stimulation. In two experiments, <em>N</em>=45 and <em>N</em>=41 participants were first trained to produce aversive, neutral, or no imagery in response to one of three different visual imagery cues. In a subsequent imagery-based differential conditioning paradigm, each of the three cues systematically co-terminated with one of three different neutral faces. Although the face that was paired with the aversive imagery cue was never paired with aversive external stimuli or threat-related instructions, participants rated it as more arousing, unpleasant, and threatening and displayed relative fear bradycardia and fear-potentiated startle. These results could be relevant for the development of fear and related disorders without trauma.</p>
Plant regeneration in leaf culture of Centaurium erythraea Rafn. Part 3: de novo transcriptome assembly and validation of housekeeping genes for studies of in vitro morphogenesis
<p>Six centaury transcriptomes (embryogenic calli, globular somatic embryos, cotyledonary somatic embryos, adventitious buds, leaves and roots of <em>in vitro</em> grown plants) were sequenced and <em>de novo</em> assembled using <a href="https://github.com/trinityrnaseq/trinityrnaseq/wiki">Trinity</a> .</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/CE_Assembly.tar.gz">CE_Assembly.tar.gz</a> - Centaury referent transcriptome comprises of 160.839 Trinity transcripts grouped in 105.726 Trinity genes.</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/CE_Assembly_fpkm.tar.gz">CE_Assembly_fpkm.tar.gz</a> - fpkm normalized read counts of the assembled transcripts in the six sequenced centaury tissues.</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/nt.db_CE_assembly.tar.gz">nt.db_CE_assembly.tar.gz</a> - annotation of assembled transcripts by mapping them against NCBI nucleotide (NT) database using BLASTn . The obtained results were filtered with E-value E ≤ 10<sup>-3</sup>.</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/swissprot.db_CE_assembly.tar.gz">swissprot.db_CE_assembly.tar.gz</a> - annotation of assembled transcripts by mapping them against NCBI nucleotide (<a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/swissprot.db_CE_assembly.tar.gz">s</a>wissprot) database using BLASTx . The obtained results were filtered with E-value E ≤ 10<sup>-3</sup>.</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/pfam30.db_CE_assembly.tar.gz">pfam30.db_CE_assembly.tar.gz</a> - annotation of assembled transcripts by mapping them against Pfam30 domain database using hmmer3. The obtained results were filtered with independent E-value E ≤ 10<sup>-3</sup>.</p>
Training material for de novo transcriptome reconstruction from RNA-seq data
<p>The data provided here are part of a Galaxy tutorial that analyzes RNA-seq data from a study published by Wu et al., 2014 (DOI:10.1101/gr.164830.113). The goal of this study was to investigate "the dynamics of occupancy and the role in gene regulation of the transcription factor Tal1, a critical regulator of hematopoiesis, at multiple stages of hematopoietic differentiation." To this end, RNA-seq libraries were constructed from multiple mouse cell types including G1E - a GATA-null immortalized cell line derived from targeted disruption of GATA-1 in mouse embryonic stem cells - and megakaryocytes. This RNA-seq data was used to determine differential gene expression between G1E and megakaryocytes and later correlated with Tal1 occupancy. This dataset (GEO Accession: GSE51338) consists of biological replicate, paired-end, polyA selected RNA-seq libraries. Because of the long processing time for the large original files, we have downsampled the original raw data files to include only reads that align to chromosome 19 and a subset of interesting genomic loci identified by Wu et al.</p>
De novo transcriptome assembly of hyperaccumulating Noccaea praecox
<p>Trinity de novo assembly for hyperaccumulating plant species Noccaea praecox (syn. Thlaspi praecox), Brassicaceae. The dataset includes annotations from SwissProt, Pfam, Rfam databases and information on transmembrane regions and signal peptide cleavage sites (annotated using BLAST, HMMER, infernal, tmHMM and signalP through Trinotate). Detailed information on the preprocessing, assembly, post-processing and annotations are described in the ReadMe file.</p> <p>Supplementary material for Bočaj, V., Pongrac, P., Fischer, S. <em>et al.</em> <em>De novo</em> transcriptome assembly of hyperaccumulating <em>Noccaea praecox</em> for gene discovery. <em>Sci Data</em> <strong>10</strong>, 856 (2023). <a href="https://doi.org/10.1038/s41597-023-02776-x">https://doi.org/10.1038/s41597-023-02776-x</a></p>
De novo sequencing of phages T4 and T7
<p>Raw data and assemblies of the <em>de novo </em>sequencing of the "model" phages T4 and T7, performed with Illumina NextSeq 2x150 and Oxford Nanopore, generated for the "Phage Annotation Workshop" held online on November 2021:</p> <p>https://github.com/quadram-institute-bioscience/phage-annotation-workshop/</p>
Ramonda serbica de novo transcriptome database
<p>Ramonda serbica de novo transcriptome database obtained from desiccated and hydrated leaves.</p>
The Human Developing Cerebral Cortex Is Characterized by an Elevated De Novo Expression of Long Noncoding RNAs in Excitatory Neurons
<p>This project contains the annotated transcriptomes in GTF format used in the manuscript "The Human Developing Cerebral Cortex Is Characterized by an Elevated De Novo Expression of Long Noncoding RNAs in Excitatory Neurons" DOI: <a href="https://doi.org/10.1093/molbev/msae123">https://doi.org/10.1093/molbev/msae123</a></p>
Genome-wide de novo L1 Retrotransposition Connects Endonuclease Activity with Replication: insertion data and derivative models
<p>This data repository provides access to the LINE-1 (L1) insertion site data from Flasch, et al., 2019:<br><a href="https://www.sciencedirect.com/science/article/pii/S0092867419302338?via%3Dihub">https://www.sciencedirect.com/science/article/pii/S0092867419302338?via%3Dihub</a></p> <p>Please see file <strong>L1_actual_and_random_insertions_help.docx</strong> for more detailed information.</p> <p>Files <strong>weighted_model_142_102917_corrected.txt</strong> and <strong>weighted_model_142_102917_uncorrected.txt</strong> carry a list of all possible 7-mer insertion sites, one per row, with site weights calculated based on observed L1 insertion sites. The files are either corrected or uncorrected for the frequency of those sites as found in the human genome, respectively. A header line defines the columns.</p> <p>The weight files described above were used to construct the simulated <strong>hg19 </strong>insertions sets described below.</p> <p>Archive <strong>all_insertion_sets.tar</strong> contains a series of insertion files, each with the complete data set used to analyze insertions from the named cell line.</p> <p>Column 5 is the iteration number, where:</p> <ul> <li>iteration == 0 identifies the actual, observed insertions</li> <li>each iteration > 0 identifies one round of simulation, up to 10K total simulations</li> <li>each iteration has the same number of insertions</li> </ul> <p>Column 4 is the insertion number within each actual or simulated insertion set.</p> <p>Please see the companion Zenodo data set:<br>10.5281/zenodo.12538130<br>for more information about creating insertion site models from your own insertion data.</p>
Genome-wide de novo L1 Retrotransposition Connects Endonuclease Activity with Replication: creating new models
<p>This data repository provides code and general instructions for creating new LINE-1 (L1) insertion site models as described in Flasch, et al., 2019:<br><a href="https://www.sciencedirect.com/science/article/pii/S0092867419302338?via%3Dihub">https://www.sciencedirect.com/science/article/pii/S0092867419302338?via%3Dihub</a></p> <p>Please see file <strong>L1_Simulation_Files_help.docx</strong> for more detailed information.</p> <p>File <strong>L1Simulation_filelist.xlsx</strong> lists the files described in the Word file and found in <strong>L1Simulations.tar.gz</strong>.</p> <p>Required large file <strong>ChrmsALL_table_sortEN.bed.gz</strong> is found individually. Importantly, like the paper analysis, this file is specific to the <strong>hg19 </strong>version of the human genome.</p> <p>Please see the companion Zenodo data set<br>10.5281/zenodo.8233858<br>if you only want to access our insertion data and the resulting models we created.</p> <p> </p>
Supplementary data and scripts for Willemsen et al., 2019 "Genome plasticity in Papillomaviruses and de novo emergence of E5 oncogenes"
<p>Supplementary data for Willemsen et al., 2019 "Genome plasticity in Papillomaviruses and <em>de novo</em> emergence of E5 oncogenes". The data set consists of three folders: “Alignments”, “Bali-Phy” and “RandomPermutationTests”. The “Alignments” folder contains the different alignments used for phylogenetic tree construction and comparison. The “Bali-Phy” folder contains the final results and convergence diagnostics of the Common Ancestry tests obtained by using the Bali-Phy software. The “RandomPermutationTests” folder contains all the data and scripts to repeat the random permutation tests described in the manuscript. Please see the corresponding README files for more information.</p>
De novo genome assembly of the meadow brown butterfly, Maniola jurtina
<p>1. Whole-genome GFF file (raw and filtered for min. gene length) [<em>Maniola.jurtina.gff3</em>, <em>Maniola_jurtina_filtered.gff3</em>]</p> <p>2. List of <em>M. jurtina</em> proteins [<em>Mjurtina_proteins.fa</em>].</p> <p>3. Results of spot pattern genes BLAST against <em>M. jurtina</em> proteome [<em>Lepidoptera_MJ_protein_matches.xlsx</em>]. </p> <p>4. Annotations [blast2go_export.txt]</p>
Genome-wide tool for rapid de novo identification and visualisation of interspersed and tandem
<p><span>Genomic repeats are functionally ubiquitous structural units found in all genomes. Studying these repeats of different origins is essential for the evolution and adaptation of a given organism. These repeating patterns have manifold signatures and structures with varying degrees of homology, making their identification challenging. To address this challenge, we developed a new algorithm and software that can rapidly and accurately detect any repeated sequences <em>de novo</em> with varying degrees of homology in genomic sequences in interspersed or clustered repeats. Numerous forms of repeated sequences and complex patterns can be identified, even for complex sequence variants and implicit or mixed types of repeat blocks. Direct and inverted-repeat elements, perfect and imperfect microsatellite repeats, and any short- or long-tandem repeat belonging to a wide range of higher-order repeat structures of telomers or large satellite sequences can be detected. By combining precision and versatility, our tool contributes significantly to elucidating the intricate landscape of genomic repeats.</span></p>
gnomAD polymorphism and de novo mutation data for analysis of mutation rates in highly mutable gene classes
<p>We analyze the human mutation rate in three gene classes (IGK, RNU, and tRNA) which deviate from the expectations of a mutation rate model. We examine the distribution of allele frequencies for SNVs within these genes and we analyze the counts of de novo mutations stratified by whether the SNV was observed or not. </p> <p>{CHR}_IGK_SFS_v2_denovo.gz: allele frequencies, mutation rate estimates, and whether the de novo mutation was observed for IGK, RNU, and tRNA genes. Based on gnomAD v3. </p> <p>{CHR}_indiv_mu.csv: quality information for variants in these gene classes from the 1kg subset of gnomAD.</p> <p>"CHR", "POS", "REF", "ALT", "FILTER", "AC", "AN", "MQRankSum", "pab_max", "VQSLOD", "AB", "PN", "MR", "AR", "MG", "MC", "QUAL"</p> <p>all_variants_chr21_mu_h.csv.gz: all variants from chromosome 21 to use for comparing allele frequencies to those in our gene classes.</p> <p>21_indiv_mu_all.csv.gz: quality information from all variants on chromosome 21 from the 1kg subset of gnomAD to use for comparison with gene classes.</p> <p>"CHR", "POS", "REF", "ALT", "FILTER", "AC", "AN", "MQRankSum", "pab_max", "VQSLOD", "AB", "PN", "MR", "AR", "MG", "MC", "QUAL"</p> <p> </p>
Draft de novo genome assemblies of a male and female Amphibolurus muricatus (jacky dragon)
<p>Four de novo nuclear genome assemblies of <em>Amphibolurus muricatus</em></p> <p><strong>Assembly 1.0: A 10x Genomics linked-read sequencing assembly</strong><br> • AmpMurF_1.0.fa.tar.gz (female <em>A. muricatus</em>)<br> • AmpMurM_1.0.fa.tar.gz (male <em>A. muricatus</em>)</p> <p><strong>Assembly 1.1: Further scaffolding of assembly 1.0 using RNA-seq data</strong><br> • AmpMurF_1.1.fa.tar.gz (female <em>A. muricatus</em>)<br> • AmpMurM_1.1.fa.tar.gz (male <em>A. muricatus</em>)</p> <p><strong>Assembly 2.0: Further scaffolding of assembly 1.0 using SLR-superscaffolder</strong><br> • AmpMurF_2.0.fa.tar.gz (female <em>A. muricatus</em>)<br> • AmpMurM_2.0.fa.tar.gz (male <em>A. muricatus</em>)</p> <p><strong>Assembly 3.0: An stLFR linked-read sequencing assembly</strong><br> • AmpMurF_3.0.fa.tar.gz (female <em>A. muricatus</em>)<br> • AmpMurM_3.0.fa.tar.gz (male <em>A. muricatus</em>)</p> <p><strong>Methods<br> Assembly 1.0: A 10x Genomics linked-read sequencing assembly</strong><br> Male and female <em>A. muricatus</em> genome sequencing libraries were constructed on the Chromium system (10x Genomics, Pleasanton, CA, USA) by the Ramaciotti Centre for Genomics (Sydney, Australia). The Chromium instrument enables unique barcoding of long stretches of DNA on gel beads. The barcodes allow later reconstruction of long DNA fragments from a series of short DNA fragments with the same barcode (i.e., linked-reads). After barcoding, DNA was sheared into smaller fragments and sequenced on the NovaSeq 6000 platform (Illumina, CA, USA) to generate 151 bp paired-end (PE) reads. A total of 904.9 M raw 10x Genomics Chromium linked-reads were generated. Raw 10x data were assembled with Supernova v2.1.1 (Weisenfeld et al., 2017) and a FASTA file was generated using the ‘pseudohap style’ option in Supernova mkoutput. All female (~450 M) and male (~550 M) read pairs were utilised (female sequencing depth ca 50.3×; male, ca 47.8×). The resulting assemblies was further scaffolded with ARKS v1.0.3 (Coombe et al., 2018), reusing the 10x reads, and the companion LINKS program (v1.8.7) (Warren et al., 2015). ARKS employs a <em>k</em>-mer approach to map linked barcodes to the contigs in the initial Supernova assembly to generate a scaffold graph with estimated distances for LINKS input. These assemblies were denoted AmpMurF_1.0 (female) and AmpMurM_1.0 (male). We used GapCloser v1.12 (part of SOAPdenovo2) (Luo et al., 2012) to fill gaps in the assembly. GapCloser was run using the parameter -l 150) and clean 10x Genomics reads PE reads. </p> <p><strong>Assembly 1.1: Further scaffolding using RNA-seq data</strong><br> We attempted to improve the v1.0 genome assemblies’ contiguity using RNA-sequencing reads. RNA-seq reads (from brain, ovary, and testis; see below) were filtered (i.e., cleaned) to remove adapters and low-quality reads using Flexbar v3.4.0 and used to further re-scaffold the v1.0 assemblies (FASTA files before gapclosing) with P_RNA_scaffolder (Zhu et al., 2018). The default Flexbar settings discards all reads with any uncalled bases. A final round of scaffolding was performed on the resulting assemblies using L_RNA_scaffolder (Xue et al., 2013). These assemblies were denoted AmpMurF_1.1 (female) and AmpMurM_1.1 (male). As before, GapCloser and clean 10x Genomics reads were used to fill gaps. </p> <p><strong>Assembly 2.0: Further scaffolding using SLR-superscaffolder</strong><br> As an alternative approach, we attempted to improve the v1.0 genome assemblies’ contiguity using SLR-superscaffolder (Guo et al., 2021). Briefly, SLR-superscaffolder employs single tube long fragment read (stLFR) sequencing (Wang et al., 2019) reads (see section below) to generate hybrid genome assemblies. The software was run with default parameters except for PE_SEED_MIN=300 (minimum contig size to fill; default 1000). These assemblies were denoted AmpMurF_2.0 (female) and AmpMurM_2.0 (male). GapCloser and clean stLFR reads (with the barcode removed using https://github.com/BGI-Qingdao/stLFR_barcode_split) were used to fill gaps. </p> <p><strong>Assembly 3.0: An stLFR linked-read sequencing and supernova assembly</strong><br> We also generated independent assemblies for the individuals sequenced on the 10x Genomics Chromium system using single tube long fragment read (stLFR) sequencing (Wang et al., 2019). BGI (Brisbane, Australia) generated ~100×-coverage 100-bp paired-end reads (plus a 42-bp stLFR barcode on the right/_2 read). Low-quality reads, PCR duplicates, and adaptors were removed using SOAPnuke v1.5 (Chen et al. 2018). The stLFRdenovo pipeline (<a href="https://github.com/BGI-biotools/stLFRdenovo">https://github.com/BGI-biotools/stLFRdenovo</a>), which is based on Supernova and customized for stLFR data, was used to generate a <em>de novo</em> genome assembly. The stLFRdenovo tool ‘FillGaps’ was used to fill gaps.</p> <p><strong>References</strong><br> Chen, Y., Chen, Y., Shi, C., Huang, Z., Zhang, Y., Li, S., Li, Y., Ye, J., Yu, C., Li, Z., et al. (2018). SOAPnuke: a MapReduce acceleration-supported software for integrated quality control and preprocessing of high-throughput sequencing data. Gigascience 7, 1-6.<br> Coombe, L., Zhang, J., Vandervalk, B.P., Chu, J., Jackman, S.D., Birol, I., and Warren, R.L. (2018). ARKS: chromosome-scale scaffolding of human genome drafts with linked read kmers. BMC Bioinformatics 19, 234.<br> Guo, L., Xu, M., Wang, W., Gu, S., Zhao, X., Chen, F., Wang, O., Xu, X., Seim, I., Fan, G., et al. (2021). SLR-superscaffolder: a de novo scaffolding tool for synthetic long reads using a top-to-bottom scheme. BMC Bioinformatics 22, 158.<br> Luo, R., Liu, B., Xie, Y., Li, Z., Huang, W., Yuan, J., He, G., Chen, Y., Pan, Q., Liu, Y., et al. (2012). SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 1, 18.<br> Wang, O., Chin, R., Cheng, X., Wu, M.K.Y., Mao, Q., Tang, J., Sun, Y., Anderson, E., Lam, H.K., Chen, D., et al. (2019). Efficient and unique cobarcoding of second-generation sequencing reads from long DNA molecules enabling cost-effective and accurate sequencing, haplotyping, and de novo assembly. Genome Res 29, 798-808.<br> Warren, R.L., Yang, C., Vandervalk, B.P., Behsaz, B., Lagman, A., Jones, S.J., and Birol, I. (2015). LINKS: Scalable, alignment-free scaffolding of draft genomes with long reads. Gigascience 4, 35.<br> Weisenfeld, N.I., Kumar, V., Shah, P., Church, D.M., and Jaffe, D.B. (2017). Direct determination of diploid genome sequences. Genome Res 27, 757-767.<br> Xue, W., Li, J.T., Zhu, Y.P., Hou, G.Y., Kong, X.F., Kuang, Y.Y., and Sun, X.W. (2013). L_RNA_scaffolder: scaffolding genomes with transcripts. BMC Genomics 14, 604.<br> Zhu, B.H., Xiao, J., Xue, W., Xu, G.C., Sun, M.Y., and Li, J.T. (2018). P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads. BMC Genomics 19, 175.</p>
Figs. 1-3 in Um Novo Gênero De Ochlerini Do Sul Do Brasil (Heteroptera, Pentatomidae, Discocephalinae)
Figs. 1-3. Ocellatocorisdasys, sp. nov., holótipo,: 1 dorsal, comprimentototal: 13,4mm; 2, contornodopronoto, dorsal; 3, placas genitais, ventral (es, espiráculo; gc8, gonocoxito 8; gc9, gonocoxito 9; la8, laterotergito 8; la9, laterotergito 9; VII, sétimo urosternito).
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.