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Figure 2. PAM250 matrix for the encoded sequence-Secondary Structure Prediction of Protein using Resilient Back Propagation Learning Algorithm
<p>The PAM matrix (Dayhoff et al., 1978) describes the probability that original amino acid<br> will be replaced by another amino acid over a defined evolutionary interval. The unit of<br> evolutionary divergence is defined as the interval in which 1% of the amino acids have been<br> changed between two sequences. The work uses PAM250, which assumes the occurrence of 250-<br> point mutations per 100 amino acids.<br> So, for the given the protein sequence GIVEQCCASVCSLYQLENYCN, A will be replaced<br> by 1 -3 0 1 -3 -1 0 5 -2 -3 -4 -2 -3 -5 0 1 0 -7 -5 -1 as shown in Figure 2.</p>
BRAIN Journal-Two new software behavioral design patterns: Obligation Link and History Reminder-Figure 5. The Sequence Diagram of the "History Reminder" design pattern
<p>Analyzing the two main classes HistoryReminder and HistoryReminderOriginator of the “History Reminder” design pattern, we find that these two classes act as actors of the whole sequence of operations. The sequence diagram of the “History Reminder” design pattern is given below in Figure 5.</p>
BRAIN Journal-Two new software behavioral design patterns: Obligation Link and History Reminder-Figure 1. The sequence diagram of the "Obligation Link" design pattern
<p>A sequence diagram is used to model the flow of the logic of the system. A sequence diagram represents perhaps the most popular Unified Modelling Language (UML) diagram that describes the behavior of a scheme. Figure 1 shows the sequence diagram of “Obligation Link” design pattern.</p>
BRAIN Journal-A Synoptic of Software Implementation for Shift Registers Based on 16th Degree Primitive Polynomials-Figure 4. Scheme for the polynomial with [16, 14, 13, 11] tap sequence
<p>A simulation program for the functioning on LFSR of the 16th degree for the Galois implementation was developed. In the following example an analysis for the 14 selected primitive polynomials will be presented. A list with the positions which will influence the future state is called tap sequence.</p> <p>This sequence can be represented by a polynomial mod 2, only with coefficients 1 and 0, called Feedback Polynomial or Characteristic Polynomial. For the above scheme this polynomial is: P(X)= X^16+X^14+X^13+X^11+1</p>
BRAIN Journal-Novel Detection Features for SSVEP Based BCI: Coefficient of Variation and Variation Speed-Figure 3: (fi) sequences at different frequencies
<p>In Equation 4, f<sub>nbk</sub> defines neighboring frequency and L defines number of neighboring. ► sequences are shown graphically in Figure 3. </p> <p>The first developed parameter for the stability of SSVEP is the coefficient of variation (CV). The variation in <span class="math-tex">\( (fi)\)</span> sequence that is obtained at EEG component with SSVEP response is expected to be less than the other sequences. . Equation 5 shows the calculation of CV. <span class="math-tex">\( ( ) i f \)</span> standard deviation of (f<sub>i</sub>) sequence. ( ) i f is the averaged value of (f<sub>i</sub>) sequence. </p>
Enumeration of Williamson sequences divisible by 2 or 3
<p>These files contain an enumeration of all inequivalent Williamson sequences of orders divisible by 2 or 3 and up to 70 as defined in the paper "<a href="https://cs.uwaterloo.ca/~cbright/reports/jsc-willsat.pdf">Applying Computer Algebra Systems with SAT Solvers to the Williamson Conjecture</a>" by <a href="https://cs.uwaterloo.ca/~cbright/">Bright</a>, <a href="http://web.wlu.ca/science/physcomp/ikotsireas/">Kotsireas</a>, and <a href="https://ece.uwaterloo.ca/~vganesh/">Ganesh</a>.</p> <p>Every line in each file contains exactly one Williamson sequence, with spaces separating the members A, B, C, and D of the Williamson sequences. The sequence entries are encoded using the characters + for 1 and - for −1.</p> <p>A <a href="https://uwaterloo.ca/mathcheck/download/williamson-sequences">table with the sequence counts</a> in each file is also available.</p>
Adapter sequences used for trimming of genomic sequences in the assembly of the Northern Spotted Owl (<i>Strix occidentalis caurina</i>) genome assembly version 1.0
<p>These files provide the sequences of the adapters used in the construction of the genomic libraries Hanna et al. (2017a) sequenced and used to assemble the Northern Spotted Owl (<em>Strix occidentalis caurina</em>) genome assembly version 1.0 (Hanna et al. 2017b). These files also contain relevant supplemental adapter sequences from the adapter files included with Trimmomatic version 0.36 (Bolger, Lohse & Usadel, 2014).</p> <p><strong>SRR4011595_adapters.fa</strong> : This FASTA format file contains the full length sequences of the adapters Hanna et al. (2017a) used to construct the genomic library they sequenced to produced the data uploaded as NCBI Sequence Read Archive (SRA) run accession SRR4011595. I have also included the partial adapter sequences provided in the "TruSeq3-PE-2.fa" and "NexteraPE-PE.fa" files distributed with Trimmomatic version 0.36 (Bolger, Lohse & Usadel, 2014).</p> <p><strong>SRR4011596_adapters.fa</strong> : This FASTA format file contains the full length sequences of the adapters Hanna et al. (2017a) used to construct the genomic library they sequenced to produced the data uploaded as NCBI Sequence Read Archive (SRA) run accession SRR4011596. I have also included the partial adapter sequences provided in the "TruSeq3-PE-2.fa" and "NexteraPE-PE.fa" files distributed with Trimmomatic version 0.36 (Bolger, Lohse & Usadel, 2014).</p> <p><strong>SRR4011597_adapters.fa</strong> : This FASTA format file contains the full length sequences of the adapters Hanna et al. (2017a) used to construct the genomic library they sequenced to produced the data uploaded as NCBI Sequence Read Archive (SRA) run accession SRR4011597. I have also included the partial adapter sequences provided in the "TruSeq3-PE-2.fa" and "NexteraPE-PE.fa" files distributed with Trimmomatic version 0.36 (Bolger, Lohse & Usadel, 2014).</p> <p><strong>SRR4011614_adapters.fa</strong> : This FASTA format file contains the full length sequences of the adapters Hanna et al. (2017a) used to construct the genomic library they sequenced to produced the data uploaded as NCBI Sequence Read Archive (SRA) run accession SRR4011614. I have also included the partial adapter sequences provided in the "TruSeq3-PE-2.fa" and "NexteraPE-PE.fa" files distributed with Trimmomatic version 0.36 (Bolger, Lohse & Usadel, 2014).</p> <p><strong>SRR4011615_adapters.fa</strong> : This FASTA format file contains the full length sequences of the adapters Hanna et al. (2017a) used to construct the genomic library they sequenced to produced the data uploaded as NCBI Sequence Read Archive (SRA) run accession SRR4011615. I have also included the partial adapter sequences provided in the "TruSeq3-PE-2.fa" file distributed with Trimmomatic version 0.36 (Bolger, Lohse & Usadel, 2014).</p> <p><strong>SRR4011616_adapters.fa</strong> : This FASTA format file contains the full length sequences of the adapters Hanna et al. (2017a) used to construct the genomic library they sequenced to produced the data uploaded as NCBI Sequence Read Archive (SRA) run accession SRR4011616. I have also included the partial adapter sequences provided in the "TruSeq3-PE-2.fa" file distributed with Trimmomatic version 0.36 (Bolger, Lohse & Usadel, 2014).<br> <br> <strong>SRR4011617_adapters.fa</strong> : This FASTA format file contains the full length sequences of the adapters Hanna et al. (2017a) used to construct the genomic library they sequenced to produced the data uploaded as NCBI Sequence Read Archive (SRA) run accession SRR4011617. I have also included the partial adapter sequences provided in the "TruSeq3-PE-2.fa" file distributed with Trimmomatic version 0.36 (Bolger, Lohse & Usadel, 2014).</p>
Time-lapse (4D) volumetric fluorescence microscopy image sequence of a living zebrafish embryo
<p>The dataset contains a time-lapse (4D) volumetric fluorescence microscopy image sequence of a living zebrafish embryo (cxcr4aMO). The sequence has been captured with a confocal laser-scanning microscope during zebrafish gastrulation and shows endodermal cells that have been fluorescently labelled.</p> <p>The sequence is best viewed with Fiji (https://fiji.sc/) and can be loaded into Matlab with tiffread.m (http://www.cytosim.org/misc/index.html).</p> <p>For the treatment of the specimen see:</p> <p>S. Nair and T. F. Schilling. Chemokine signaling controls endodermal migration during zebrafish gastrulation. Science, 322(5898):89–92, October 2008.</p>
Influence of storm sequencing and beach recovery on sediment transport and beach resilience data set at CIEM large scale wave flume.
<p>The Influence of storm sequencing and beach recovery on sediment transport and beach resilience (RESIST) experiments project proposes to study experimentally sequences of storm induced erosion and beach recovery, with a particular focus on the poorly known morphodynamic processes under low energy conditions. Series of large scale experimental tests were done to collect data on the cross-shore hydrodynamics, sediment transport and beach evolution. The main aim of this proposal is to investigate the influence of sequences of beach erosion-recovery in the overall beach profile evolution.</p> <p>The tested wave conditions (2 erosive and 3 Accretive bichromatic conditions) were combined to form three sequences of changing high/mild energy conditions. Each condition started from an initial beach 1/15 handmade profile.</p> <p>The experiments were carried out in the large scale wave flume CIEM at Universitat Politècnica de Catalunya (UPC), Barcelona within the program of Transnational Access of Hydralab+.</p> <p>Due to its size, the data set can not be placed on this repository and will be provided on demand. Please contact with the authors or with the data manager of the CIEM installation.</p>
Biased RNG Bit Sequences, Dependent RNG Bit Sequences
<p>Matlab PRNG generated biased bit sequences without correlations and unbiased bit sequences with bit correlations; used for validation of the tests in Publication: https://doi.org/10.5281/zenodo.1286723</p>
SILVA_123 Eukaryota taxonomic training data formatted for DADA2; plus version with (uncurrated) additional sequences
<p>This is the Silva123 taxonomy reformatted to work with eukaryote sequences for dada2:</p> <p><a href="https://zenodo.org/api/files/4f873b5b-fe02-4344-8c8b-c723c3caba67/SILVA_123_dada2.fasta">SILVA_123_dada2.fasta </a></p> <p>It has been created using a script available <a href="https://github.com/derele/AA_Hyena/blob/master/R/convert_silva_taxonomy.r">here</a>.</p> <p>To increase coverage (Silva has a low coverage for eukaryotes). Uncurrated additional sequences similar to ASVs found in the intestine of hyenas (BLAST) have been added. The script used for taxonomic annotation of these sequences is available <a href="https://github.com/derele/AA_Hyena/blob/master/scripts/blast2alltax_outfmt11.pl">here</a>. The file containing these additional (uncurrated!) sequences is:</p> <p><a href="https://zenodo.org/api/files/4f873b5b-fe02-4344-8c8b-c723c3caba67/SILVA_123_dada2_exp.fasta?versionId=78a7526a-72e0-4707-ab5c-297671b5ff13">SILVA_123_dada2_exp.fasta </a></p> <p>This expanded file has been used for taxonomic annotation in: </p> <p><a href="https://doi.org/10.3389/fcimb.2017.00262">Heitlinger, E., Ferreira, S., Thierer, D., Hofer, H., & East, M. L. (2017). The intestinal eukaryotic and bacterial biome of spotted hyenas: the impact of social status and age on diversity and composition. <em>Frontiers in cellular and infection microbiology</em>, <em>7</em>, 262.</a></p>
K-mer databases of plant virus sequences for use with the Kodoja workflow
<p><strong>Details</strong></p> <p>This is a gzipped tar file that includes the plant virus database files required to run the Kodoja workflow (https://github.com/abaizan/kodoja)[1]. Kodoja is a workflow for the detection of plant virus sequences in RNA-seq data files that uses two previoulsy published tools Kraken[2] and Kaiju[3].</p> <p>This file contains databases for Kraken [2] and Kaiju [3]. The file includes the kraken database files: database.idx, database.kdb, nodes.dmp, names.dmp and the kaiju database file kaij_library.fmi.</p> <p>These k-mer databases are based on virus sequences in RefSeq [4] (ttps://www.ncbi.nlm.nih.gov/refseq/) with plant hosts as defined in the Virus-Host Database [5] (https://www.genome.jp/virushostdb/).</p> <p><strong>Version</strong><strong> 1.0</strong></p> <p>kodojaDB_v1.0 is based on RefSeq v89 and the Virus-Host Database (accessed 03/09/2018 which is based on RefSeq 89 and Genbank 226.0). The viral partition of RefSeq v89 genome comprises 7946 viruses (ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/viral/assembly_summary.txt).</p> <p>kodojaDB_v1.0 was created using kodoja_retrieve.py which is part of the kodoja workflow (v0.05) (https://github.com/abaizan/kodoja).</p> <p><strong>References</strong></p> <p>[1] Baizan-Edge, A, Cock, P, MacFarlane, S, McGavin, W, Torrance, T, Jones, S. Kodoja: A workflow for virus detection in plants using k-mer analysis of RNA-sequencing data (under review Nucleic Acids Research). </p> <p>[2] Wood,D.E. and Salzberg,S.L. (2014) Kraken: ultrafast metagenomic sequence classification using exact alignments. <em>Genome Biol.</em>, <strong>15</strong>, R46</p> <p>[3] Menzel,P., Ng,K.L. and Krogh,A. (2016) Fast and sensitive taxonomic classification for metagenomics with Kaiju. <em>Nat. Commun.</em>, <strong>7</strong>, 1–9.</p> <p>[4] O’Leary,N.A., Wright,M.W., Brister,J.R., Ciufo,S., Haddad,D., McVeigh,R., Rajput,B., Robbertse,B., Smith-White,B., Ako-Adjei,D., <em>et al.</em> (2016) Reference sequence (RefSeq) database at NCBI: Current status, taxonomic expansion, and functional annotation. <em>Nucleic Acids Res.</em>, <strong>44</strong>, D733–D745.</p> <p>[5] Mihara,T., Nishimura,Y., Shimizu,Y., Nishiyama,H., Yoshikawa,G., Uehara,H., Hingamp,P., Goto,S. and Ogata,H. (2016) Linking virus genomes with host taxonomy. <em>Viruses</em>, <strong>8</strong>, 10–15</p>
Supplement data for the article "The impact of OTU sequence similarity threshold on diatom-based bioassessment: A case study of the rivers of Mayotte (France, Indian Ocean)", in preparation
<p>These are supplement data for the article "The impact of OTU sequence similarity threshold on diatom-based bioassessment: A case study of the rivers of Mayotte (France, Indian Ocean)", in preparation</p> <p>The folowing files are available:</p> <ul> <li>Supplement 1. Map of Mayotte with the sampling sites and the rivers.</li> <li>Supplement 2. <em>rbcL</em> primers, reaction mixture, and conditions used for the PCR of the 312-bp <em>rbcL</em> fragment. The information provided is for a single reaction with a final volume of 25µL.</li> <li>Supplement 3. The 20 fastq files containing the demultiplexed DNA reads.</li> <li>Supplement 4. Number of sequence reads for each sample before and after the trimming procedure.</li> <li>Supplement 5. The 20 OTU lists, corresponding to the 20 SSTs, including the number of DNA reads within the 90 samples and their assigned taxonomy.</li> <li>Supplement 6. Sampling site description with sample codes, names of rivers, year, number of raw DNA reads and GPS coordinates.</li> <li>Supplement 7. Values and summary statistics for the environmental variables.</li> <li>Supplement 8. The script used in Mothur for the bioinformatic analysis from trimming to the used OTU lists.</li> </ul> <p> </p>
Structural modelling results to accompany the paper "Uncommon mutational profiles of metastatic colorectal cancer detected during routine genotyping using next generation sequencing: an update"
<p>This repository contains the results of modelling missense mutants in KRAS, NRAS and BRAF observed in our study in the corresponding protein structures. Modelling was performed using FoldX.</p>
Example data for "Sunbeam: an extensible pipeline for analyzing metagenomic sequencing experiments" [Version 2]
<p>This repository contains the example datasets analyzed in the Sunbeam paper, version 2. Please see the current <a href="http://sunbeam.readthedocs.io/en/latest/quickstart.html">Sunbeam Quickstart Guide</a> for up-to-date instructions on installing and running Sunbeam.</p>
Hybrid sequencing reveals insight into heat sensing and signaling of bread wheat
<p>Wheat (<em>Triticum aestivum</em> L.), a globally important crop, is challenged by increasing temperatures (heat stress, HS); however, its polyploid nature, the incompleteness of its genome sequences and annotation, the lack of comprehensive HS-responsive transcriptomes and the unexplored heat sensing and signaling of wheat hinder our full understanding of its adaptations to HS. The recently released genome sequences of wheat, as well as the emerging single-molecular sequencing technologies, provides an opportunity to thoroughly investigate the molecular mechanisms of the wheat response to HS. We generated a high-resolution spatio-temporal transcriptome map of wheat flag leaves and filling grain under HS at 0 minute (m), 5 m, 10 m, 30 m, 1 hour (h) and 4 h by combining full-length single-molecular sequencing and Illumina short reads sequencing. This hybrid sequencing newly discovered 4,947 loci and 70,285 transcripts, generating the comprehensive and dynamic list of HS-responsive full-length transcripts and complementing the recently released wheat reference genome.</p>
Sample datasets for Transposon insertion sequencing analysis tutorial
<p>The dataset contains five files:</p> <ol> <li>Tnseq-Tutorial-reads.fastqsanger.gz - A subset of TnSeq reads published in `Santiago, M., Matano, L. M., Moussa, S. H., Gilmore, M. S., Walker, S., & Meredith, T. C. (2015). A new platform for ultra-high density Staphylococcus aureus transposon libraries. <em>BMC Genomics</em>, <em>16</em>(1), 1–18. http://doi.org/10.1186/s12864-015-1361-3`</li> <li>condition_barcodes.fasta - Set of barcodes to separate reads from different experimental conditions</li> <li>construct_barcodes.fasta - Set of barcodes to separate reads from different transposon constructs</li> <li>staph_aur.fasta : Genome file for <em>Staphylococcus aureus </em></li> <li>staph_aur.fasta : Annotation file for <em>Staphylococcus aureus </em></li> </ol>
Dataset - Nutrients and biomass dynamics in photo-sequencing batch reactors treating wastewater with high nutrients loadings
<p>The data set attached consists of one excel file where the data from the article “<strong>Nutrients and biomass dynamics in photo-sequencing batch reactors treating wastewater with high nutrients loadings”</strong>, published in Ecological Engineering (vol. 119, 15<sup>th</sup> August 2018, 35-44.), can be found, as well as the different equations and formulae that were used to obtain the published results.</p>
A Comprehensive Assessment of Demographic, Environmental and Host Genetic Associations with Gut Microbiome Diversity in Healthy Individuals (16S rRNA gene sequencing data)
<p>Microbiome data accompanying manuscript "A Comprehensive Assessment of Demographic, Environmental and Host Genetic Associations with Gut Microbiome Diversity in Healthy Individuals". Data is available for alpha- and beta- diversity, as well as for individual taxa both in binary and quantitative phenotypic representation. Data is available for 827 individuals that gave consent for their data to be shared outside of the Milieu intérieur consortium. </p>
Thermal based Mean-Shift Tracking performance (including 6 video sequence)
<p>I have researched novel tracking algorithm (TIR-MS : Thermal infrared based Mean-Shift) in the single pedestrian head tracking environment. </p> <p>We evaluated the tracking performance of the proposed method and attached a video with the results of the tracking. We used to summarized as tracking performance based Average Histogram Similarity and Central Difference, respectively.</p>
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.