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FIGURE 4 in Graphic correlation of the upper Eifelian to lower Frasnian (Middle-Upper Devonian) conodont sequences in the Spanish Central Pyrenees and comparison with composite standards from other areas

FIGURE 4. Graphic correlation between the La Guàrdia d'Ares section and the composite standard (third round). The numbers represent the taxa listed in the range chart (Figures 5 and 6), error boxes indicate the sampling intervals.

FIGURE 6 in Graphic correlation of the upper Eifelian to lower Frasnian (Middle-Upper Devonian) conodont sequences in the Spanish Central Pyrenees and comparison with composite standards from other areas

FIGURE 6. Conodont range chart based on the Spanish Central Pyrenean sections (continued). Precise CSU values are given in the Appendix.

FIGURE 3 in Graphic correlation of the upper Eifelian to lower Frasnian (Middle-Upper Devonian) conodont sequences in the Spanish Central Pyrenees and comparison with composite standards from other areas

FIGURE 3. Graphic correlation between the Villech section and the composite standard for the Spanish Central Pyrenees (third round). The numbers represent the taxa listed in the range chart (Figures 5 and 6), the error boxes indicate the sampling intervals. (sem./lat.: semialternans/latifossatus).

FIGURE 2 in Deciduous dentition and dental eruption sequence of Bothriogenys fraasi (Anthracotheriidae, Artiodactyla) from the Fayum Depression, Egypt

FIGURE 2. Dental terminology used to describe features of the deciduous premolars of Bothriogenys fraasi, following Bärmann and Rössner (2011).

FIGURE 5 in Graphic correlation of the upper Eifelian to lower Frasnian (Middle-Upper Devonian) conodont sequences in the Spanish Central Pyrenees and comparison with composite standards from other areas

FIGURE 5. Conodont range chart based on the Spanish Central Pyrenean sections. Precise CSU values are given in the Appendix.

FIGURE 1. 1 in Deciduous dentition and dental eruption sequence of Bothriogenys fraasi (Anthracotheriidae, Artiodactyla) from the Fayum Depression, Egypt

FIGURE 1. 1, location map of the Jebel Qatrani area, Fayum Depression. 2, stratigraphic positions and age estimates for major mammal-bearing fossil localities, following Seiffert (2006), EOB is abbreviation for Eocene Oligocene Boundary. 3, map of Jebel Qatrani area, showing different rock units, common landmarks and the approximate position of anthracothere-bearing fossil localities.

FIGURE 2. 1 in Graphic correlation of the upper Eifelian to lower Frasnian (Middle-Upper Devonian) conodont sequences in the Spanish Central Pyrenees and comparison with composite standards from other areas

FIGURE 2. 1. Map of Paleozoic rocks on the Iberian Peninsula and position of Figure 2.2 (black square), 2. Structural geological map of the Spanish Pyrenees with indication of the studied area (white square) and 2. Structural geological map of the Spanish Pyrenees with indication of the studied area (red square) and the most important faults and thrust faults, FNP: North Pyrenean Fault, CPP: Petites Pyrénées thrust fault, CFN: Frontal North Pyrenean thrust fault, CFS: Frontal South Pyrenean thrust fault [modified from Barnolas and Pujalte (2004)], 3. Map of the Devonian facies areas and subdivision of the southern facies area in the southern Spanish Pyrenees [modified from Zwart (1979)], studied area in black square, location of the sections indicated by black stars.

opencc-by-4.0May 2024View details →

Extra tables and fastq files for "Virome Sequencing Identifies H5N1 Avian Influenza in Wastewater from Nine Cities."

Tables: "mutation_analysis.xlsx" = detailed notes on variant analysis of H5N1 reads. "TEPHI_samples_H5N1_status1.xlsx" = Table of samples with metadata and H5N1 status "BioSampleObjects.txt" = Table from SRA mapping BioSample IDs to library (sample) IDs   H5N1_reads_thru_p1858: Paired-end Illumina read files (.fastq) from all samples. Includes automated H5N1 called reads from iav_serotype tool from samples that were manually validated to have H5N1 specific reads.

opencc-by-sa-4.0Jul 2024View details →

Nanopore deep sequencing as a tool to characterize and quantify aberrant splicing caused by variants in inherited retinal dystrophy genes

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opencc-by-4.0Aug 2024View details →

4 Bars Monophonic Melodies Dataset (Pitch Sequence)

This dataset is designed for applications in music information retrieval, algorithmic composition, and machine learning tasks involving symbolic music data and it consists in a collection of unique 4 bars monophonic melodies represented as MIDI pitch sequences and each accompanied by thirteen attributes obtained with computational methods. The dataset has been generated using the <a href="https://github.com/resolv-libs" target="_blank" rel="noopener">Resolv</a> system's pipelines starting from the full version of the <a href="https://colinraffel.com/projects/lmd/">Lakh MIDI Dataset</a> (a collection of 176,581 unique MIDI files). The dataset has been used to train the models described in the papers: <div> <blockquote> M. Pettenò, A. I. Mezza, and A. Bernardini, "Conditional Diffusion As Latent Constraints for Controllable Symbolic Music Generation", in Proc. of the 26th International Society for Music Information Retrieval Conference (ISMIR 2025), Daejeon, Korea, S ept. 21-25, 2025. M. Pettenò, A. I. Mezza, and A. Bernardini, "On the Joint Minimization of Regularization Loss Functions in Deep Variational Bayesian Methods for Attribute-Controlled Symbolic Music Generation", in Proc. of the 33rd European Signal Processing Conference (EUSIPCO 2025), Palermo, Italy, Sept. 8-12, 2025. </blockquote> </div> The full article of this work also contains all the details on how the attributes have been obtained and on the implementation of the pipelines used for the generation and here it is worth to point out that melodies have been quanized to 4 steps per quarter and only 4/4 time signatures have been considered, hence each melody consists of N = 64 steps where each step is a number in the range [21-108], the MIDI pitches available in a standard piano, or a token in the set {128, 129} for hold note and note off events respectively. No additional performance features (e.g., dynamics, duration, or timing) are included, making this dataset a purely pitch-based collection. Three datasets (train, validation and test) are provided as <a href="https://www.tensorflow.org/tutorials/load_data/tfrecord" target="_blank" rel="noopener">TFRecord</a> file divided into 8 shards that contain the data in the Tensorflow's <a href="https://www.tensorflow.org/api_docs/python/tf/train/SequenceExample">SequenceExample</a> format in which the feature_lists field contains the pitch sequence as a list of integers and the context field its attributes. The table below shows the numbers of unique melodies contained in the three datasets. <table> <tbody> <tr> <td> </td> <td>Train</td> <td>Validation</td> <td>Test</td> </tr> <tr> <td>Total unique melodies</td> <td>10,126,676</td> <td>70,908</td> <td>22,265</td> </tr> </tbody> </table>   And here is the list of computed attributes for each melody: <table> <tbody> <tr> <td>Attribute Name</td> <td>SequenceExample Context Key</td> <td>Description</td> </tr> <tr> <td>Toussaint Metrical Complexity</td> <td><code>toussaint</code></td> <td>A metric that measures the degree of syncopation in rhythm patterns.</td> </tr> <tr> <td>Note Density</td> <td><code>note_density</code></td> <td>Measures the density of note onsets within the melody.</td> </tr> <tr> <td>Pitch Range</td> <td><code>pitch_range</code></td> <td>An indicator of how wide or narrow the melody is in terms of its pitch content.</td> </tr> <tr> <td>Contour</td> <td><code>contour</code></td> <td>Measures the degree to which the melody moves up or down.</td> </tr> <tr> <td>Note Change Ratio</td> <td><code>note_change_ratio</code></td> <td>The number of note changes normalized to the total number of steps N.</td> </tr> <tr> <td>Dynamic Range</td> <td><code>dynamic_range</code></td> <td>The difference between the maximum and minimum note velocities.</td> </tr> <tr> <td>Longest Repetitive Section</td> <td><code>len_longest_rep_section</code></td> <td>The length of the longest repetitive section in the melody normalized to the total number of steps N. A repetitive section is defined as a note that consecutively repeats at least r = 4 times.</td> </tr> <tr> <td>Repetitive Section Ratio</td> <td><code>repetitive_section_ratio</code></td> <td>The ratio between the total number of repetitive sections and a normalization factor N/r = 64/4 = 16.</td> </tr> <tr> <td>Hold Note Steps Ratio</td> <td><code>ratio_hold_note_steps</code></td> <td>The ratio between the number steps where a note is hold and the total steps N.</td> </tr> <tr> <td>Note Off Steps Ratio</td> <td><code>ratio_note_off_steps</code></td> <td>The ratio between the number steps where no note is played and the total steps N.</td> </tr> <tr> <td>Unique Notes Ratio</td> <td><code>unique_notes_ratio</code></td> <td>The ratio of unique notes is defined with respect to the total number of MIDI pitches considered (88) and the total number of steps N.</td> </tr> <tr> <td>Unique Bigrams Ratio</td> <td><code>unique_bigrams_ratio</code></td> <td>It is the ratio of the unique bigrams in the melody with respect to the total numbers of steps N.</td> </tr> <tr> <td>Unique Trigrams Ratio</td> <td><code>unique_trigrams_ratio</code></td> <td>It is the ratio of the unique trigrams in the melody with respect to the total numbers of steps N.</td> </tr> </tbody> </table>   To access the content of a SequenceExample use the tf.io.parse_single_sequence_example, for instance: <div> <blockquote> <pre>tf.io.parse_single_sequence_example( serialized_example, context_features={ "toussaint": tf.io.FixedLenFeature([], dtype=tf.float32, default_value=0), "note_density": tf.io.FixedLenFeature([], dtype=tf.float32, default_value=0), }, sequence_features=["pitch_seq"] )</pre> </blockquote> </div>

opencc-by-4.0Aug 2024View details →

Sequencing results of the 21 resequenced herbarium tomato specimens

Sequencing results of the 21 herbarium tomato specimens resequenced on an Illumina NovaSeq 600 platform.

opencc-by-4.0Apr 2024View details →

Hieracium alpinun PAI33838 (2n = 2x = 18) Oxford Nanopore Technology sequences library

Sample 1 000 000 reads (trimmed).

Supplemental data for: Evaluation of SARS-CoV-2 response at the University of North Carolina (UNC) at Charlotte using percent positivity data and viral genomic sequence data.

Supplemental data for: Evaluation of SARS-CoV-2 response at the University of North Carolina (UNC) at Charlotte using percent positivity data and viral genomic sequence data. Submitted to Biocarla 2024 https://carla2024.org/portfolios/biocarla/ Authors: Daniel Janies 1,2,3 [0000−0002−7890−9906], Shirish Yasa 1,2,3 [0000−0003−3217−4921], Colby T. Ford 1,3,4 [0000−0002−7859−3622] Jannatul Ferdous 2,3 [0000−0003−3053−9616], William Taylor 2,3 [0009−0000−6204−1172], April Harris 2,3 [0009−0009−2557−7926], Sam Kunkleman 2,3 [0000−0002−2309−6418], Juan Bolanos 2,3, Kevin Lambirth 2,3 [0000-0002-6568-543X], Denis Jacob Machado 1,2,3 [0000−0001−9858−4515], Cynthia Gibas 1,2,3 [0000−0002−1288−9543], and Jessica Schlueter 1,2,3 [0000−0002−6490−0580] Affiliations: 1) Center for Computational Intelligence to Predict Health and Environmental Risks (CIPHER), University of North Carolina at Charlotte 28223, USA Correspondence to: djanies@charlotte.edu https://cipher.charlotte.edu 2) Department of Bioinformatics and Genomics, University of North Carolina at Charlotte 28223, USA https://cci.charlotte.edu/departments/ department-of-bioinformatics-and-genomics/ 3) College of Computing and Informatics, University of North Carolina at Charlotte 28223, USA https://cci.charlotte.edu 4) School of Data Science, University of North Carolina at Charlotte 28223, USA https://sds.charlotte.edu 5) Division of Research, University of North Carolina at Charlotte 28223, USA https://research.charlotte.edu/

opencc-by-4.0Mar 2023View details →

Figure 2 in First record of Parochlus kiefferi (Garrett, 1925) in a sediment sequence from a Slovak mountain lake with notes on paleolimnological interpretation

Figure 2. Detail of the head capsule of Parochlus kiefferi found in lake Vrbické pleso. Photo: Martina Jambrović.

opencc-by-4.0Jan 2021View details →

Fig. 1 in Polymerase chain reaction and gyrA nucleotide sequence analysis of Wolbachia endosymbionts (Rickettsiales: Anaplasmataceae) in various species of Culicidae, Cimex lectularius (Hemiptera: Cimicidae) and Dirofilaria immitis (Rhabditida: Onchocercidae)

Fig. 1. Phylogenetic tree based on Maximum Likelihood depicting the grouping of Wolbachia from various hosts based on analysis of the gyrA gene. The numerical value displayed on branches is the bootstrap value (1,000 replicates), and branches with values below 50% are collapsed. The tree illustrates that gyrA sequences distinguish Wolbachia subtypes based on host taxonomy, demonstrating that this gene may contribute to Wolbachia strain typing projects and future phylogenetic analysis.

opencc-by-4.0Jan 2024View details →

MNBC: a multithreaded Minimizer-based Naïve Bayes Classifier for improved metagenomic sequence classification

These files provide supplementary data underlying the article <a title="https://doi.org/10.1093/bioinformatics/btae601" href="https://doi.org/10.1093/bioinformatics/btae601" target="_blank" rel="noopener noreferrer nofollow">doi.org/10.1093/bioinformatics/btae601</a> (see Figure 1 in the article): <ul> <li>37345_filtered_training_and_test_genomes_list.txt: Refseq assembly sequence filenames of the 37345 filtered training and test genomes</li> <li>taxonomy_37345_filtered_training_and_test_genomes.txt: Taxonomy file for all 37345 filtered training and test genomes</li> <li>Uniform_reference_database_31991_training_genomes_assemblyID_list.txt: Refseq assembly accessions of the 31991 training genomes in the uniform reference database</li> <li>uniform_reference_database.tar.gz_1 to uniform_reference_database.tar.gz_10: Merge them into a single file using the cat command. The folder produced by decompressing this file is the uniform reference database.</li> <li>taxonomy_uniform_reference_database.txt: Taxonomy file for the uniform reference database (i.e. the 31991 training genomes)</li> <li>5354_test_genomes_assemblyID_list.txt: Refseq assembly accessions of the 5354 test genomes</li> <li>testReads_NextSeq_C0.05.fasta.gz: 6562565 150bp-long positive reads randomly generated from the 5354 test genomes, simulating reads sequenced by NextSeq (0.05 coverge)</li> <li>testReads_MiSeq_C0.05.fasta.gz: 3282728 300bp-long positive reads randomly generated from the 5354 test genomes, simulating reads sequenced by MiSeq (0.05 coverge)</li> <li>testReads_Nanopore_C0.05.fasta.gz: 181912 positive reads of normally distributed 1kb-10kb lengths randomly generated from the 5354 test genomes, simulating reads sequenced by Nanopore (0.05 coverge)</li> <li>negaReads_NextSeq_C0.05.fasta.gz: 10143 150bp-long negative reads randomly generated from Chromosome 1 of the Arabidopsis Thaliana reference genome, simulating reads sequenced by NextSeq (0.05 coverge)</li> <li>negaReads_MiSeq_C0.05.fasta.gz: 5072 300bp-long negative reads randomly generated from Chromosome 1 of the Arabidopsis Thaliana reference genome, simulating reads sequenced by MiSeq (0.05 coverge)</li> <li>negaReads_Nanopore_C0.05.fasta.gz: 277 negative reads of normally distributed 1kb-10kb lengths randomly generated from Chromosome 1 of the Arabidopsis Thaliana reference genome, simulating reads sequenced by Nanopore (0.05 coverge)</li> <li>CAMI2_reference_database_16864_genomes_list.txt: Refseq assembly sequence filenames of the 16864 genomes and chromosomes in the reference database for CAMI2</li> <li>taxonomy_CAMI2_reference_database.txt: Taxonomy file for the CAMI2 reference database</li> </ul> Tip: To directly use the taxonomy file "taxonomy_uniform_reference_database.txt", please use version v1.1 or earlier of the MNBC tool. If using later versions it needs regenerating with the "MNBC taxonomy" program.

Metagenomic investigation of the faecal microbiomes of great tits and blue tits - supplementary sequences

<h2>Overview:</h2> The vertebrate gut microbiome plays crucial roles in host health and disease. However, there is limited data on the microbiomes of wild birds, most of which is restricted to barcode sequences. We therefore explored the use of shotgun metagenomics on the faecal microbiomes of two wild bird species widely used as model organisms in ecological studies: the great tit (Parus major) and the Eurasian blue tit (Cyanistes caeruleus). Mitochondrial genomes from the host and eukaryotic pathogens that were assembled from these metagenomes and are made available as a catalogue in this archive. <h2>Methods:</h2> Metagenomic reads were trimmed, and quality controlled using FastP configured to a minimum phred score of 20 and minimum length of 50 bp. Individual sample assemblies were performed on each metagenomic sample using MEGAHIT v1.2.9. The BLAST 2.16 suite of programs was downloaded from ftp.ncbi.nlm.nih.gov/blast and used to perform homology searches of the assemblies, using the makeblastdb utility to generate libraries, the blastn and tblastx utilities to search contigs with query sequences under high stringency (e value ≥1*e-200) and the blastdbcmd utility to retrieve hits from databases. <h2>Files:</h2> <ul> <li>The Isospora_mitochondrial.fasta contains the fasta sequences for mitochondrial genomes of the bird pathogen Isospora sp, assembled from two faecal samples from the Great Tit (Parus major).</li> <li>The Cyanistes.caeruleus_mitochondrial.fasta contains the fasta sequences for mitochondrial genomes of the host bird, assembled from two faecal samples from the blue Tit (Cyanistes caeruleus).</li> <li>The Parus.major_mitochondrial.fasta contains the fasta sequences for mitochondrial genomes of the host bird, assembled from two faecal samples from the blue Tit (Cyanistes caeruleus).</li> </ul>

Representative snapshots of imaging sequences used in transcan_IDH-mutant_LGG_radiomics analysis

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opencc-by-4.0Aug 2024View details →

Sewage - deep sequencing data

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Supplementary data to the African Yam Bean Whole Genome Sequencing Project ENA Project_ID:PRJEB57813

The first chromosome-scale assembly of the African yam bean, Sphenostylis stenocarpa (Hochst. ex. A. Rich.) Harms, an original African tuberous legume producing both pods and protein-rich tubers. ENA Project_ID: PRJEB57813 Genome Assembly Accession: GCA_963425845