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Fig. 9 in Amended diagnosis and redescription of Pristimantis marmoratus (Boulenger, 1900) (Amphibia: Craugastoridae), with a description of its advertisement call and notes on its breeding ecology and phylogenetic relationships
Fig. 9. Habitat of Pristimantis marmoratus (Boulenger, 1900). Left. Submontane rainforest in Kaieteur National Park at ca 630 m elevation. Right. Montane rainforest on the slopes of Maringma-tepui, Guyana at ca 1376 m elevation. Photographs by PJRK.
Fig. 8 in Amended diagnosis and redescription of Pristimantis marmoratus (Boulenger, 1900) (Amphibia: Craugastoridae), with a description of its advertisement call and notes on its breeding ecology and phylogenetic relationships
Fig. 8. Vocalization of Pristimantis marmoratus (Boulenger, 1900); oscillogram and spectrogram obtained using Seewave v. 1.6.4 in R. Spectrogram (top) and oscillogram (below) of one call of IRSNB 14472 from Kaieteur National Park, Guyana. Call recorded at a temperature of 24°C.
Fig. 6. A in Amended diagnosis and redescription of Pristimantis marmoratus (Boulenger, 1900) (Amphibia: Craugastoridae), with a description of its advertisement call and notes on its breeding ecology and phylogenetic relationships
Fig. 6. A. Guzmania cf. sphaeroidea (André) André ex Mez, an arboreal bromeliad species used as egg deposition site by Pristimantis marmoratus (Boulenger, 1900) in the Wokomung Massif. B. Egg clutch of Pristimantis marmoratus deposited on a leaf of the arboreal bromeliad Guzmania cf. sphaeroidea in the Wokomung Massif. C. Egg clutch of Anomaloglossus beebei (Noble, 1923) (white arrow) deposited in the phytotelmata of the same plant as in B. D. Dorsolateral view of IRSNB 17916, 11.3 mm SVL, a juvenile of P. marmoratus collected on the slopes of Maringma-tepui, Guyana. Photographs A–C by DBM, D by PJRK.
Fig. 5 in Amended diagnosis and redescription of Pristimantis marmoratus (Boulenger, 1900) (Amphibia: Craugastoridae), with a description of its advertisement call and notes on its breeding ecology and phylogenetic relationships
Fig. 5. Pristimantis marmoratus (Boulenger, 1900). Intraspecific variation in dorsal (top) and ventral (below) colour patterns in preserved specimens. Photographs by PJRK.
Fig. 4 in Amended diagnosis and redescription of Pristimantis marmoratus (Boulenger, 1900) (Amphibia: Craugastoridae), with a description of its advertisement call and notes on its breeding ecology and phylogenetic relationships
Fig. 4. Pristimantis marmoratus (Boulenger, 1900) (four individuals at the top) and P. pulvinatus (Rivero, 1968) (two individuals below). Intraspecific variation in dorsal colour pattern and sexual dimorphism in living specimens. Note: the subtle hint of green visible on the lower body and legs of some specimens of P. marmoratus is due to a reflection of the substrate (green leaf). Photographs by PJRK, except the uncollected P. pulvinatus, which is by CBA.
Fig. 3 in Amended diagnosis and redescription of Pristimantis marmoratus (Boulenger, 1900) (Amphibia: Craugastoridae), with a description of its advertisement call and notes on its breeding ecology and phylogenetic relationships
Fig. 3. Pristimantis marmoratus (Boulenger, 1900). Ventral view of left hand and left foot of a male (top), and ventral view of right hand and right foot of a female (below), both from Kaieteur National Park, Guyana. Photographs by PJRK.
Fig. 2 in Amended diagnosis and redescription of Pristimantis marmoratus (Boulenger, 1900) (Amphibia: Craugastoridae), with a description of its advertisement call and notes on its breeding ecology and phylogenetic relationships
Fig. 2. Pristimantis marmoratus (Boulenger, 1900). Preserved adult ♂, holotype (BMNH 1947.2.16.92). A. Dorsal view. B. Ventral view. C. Dorsolateral view. Grid squares = 5 mm. Photographs by PJRK.
Fig. 10 in Amended diagnosis and redescription of Pristimantis marmoratus (Boulenger, 1900) (Amphibia: Craugastoridae), with a description of its advertisement call and notes on its breeding ecology and phylogenetic relationships
Fig. 10. Phylogenetic relationships within the Pristimantis "unistrigatus group" in the Guiana Shield as recovered in the MrBayes analysis (438 bp of the 16S rRNA gene sequence). Values at each node represent statistical support (* = 0.99 or 1). Pristimantis marmoratus (Boulenger, 1900) is highlighted in red.
Fig. 1 in Amended diagnosis and redescription of Pristimantis marmoratus (Boulenger, 1900) (Amphibia: Craugastoridae), with a description of its advertisement call and notes on its breeding ecology and phylogenetic relationships
Fig. 1. Map of the Eastern Pantepui District showing the known distribution of Pristimantis marmoratus (Boulenger, 1900). Red dots denote localities of confirmed occurrence based either on museum specimens or colour photographs.
Fig. 7 in Amended diagnosis and redescription of Pristimantis marmoratus (Boulenger, 1900) (Amphibia: Craugastoridae), with a description of its advertisement call and notes on its breeding ecology and phylogenetic relationships
Fig. 7. Vocalization of Pristimantis marmoratus (Boulenger, 1900); oscillograms and spectrograms obtained using Raven v. 1.4. A. Oscillogram (top) and spectrogram (below) of three calls of IRSNB 14472 from Kaieteur National Park, Guyana (ca 16 s recording). B. Expanded oscillogram (top) and spectrogram (below) of one call of IRSNB 14471 from Kaieteur National Park, Guyana. C. Expanded oscillogram (top) and spectrogram (below) of one call of IRSNB 14472 from Kaieteur National Park, Guyana. Calls recorded at a temperature of 24°C.
BirdVox-70k: a dataset for species-agnostic flight call detection in half-second clips
<p>BirdVox-70k: a dataset for avian flight call detection in half-second clips<br> ======================================================================================<br> Version 1.0, April 2018.</p> <p><br> Created By<br> ----------</p> <p>Vincent Lostanlen (1, 2, 3), Justin Salamon (2, 3), Andrew Farnsworth (1), Steve Kelling (1), and Juan Pablo Bello (2, 3).</p> <p>(1): Cornell Lab of Ornithology (CLO)<br> (2): Center for Urban Science and Progress, New York University<br> (3): Music and Audio Research Lab, New York University</p> <p>https://wp.nyu.edu/birdvox</p> <p> </p> <p>Description<br> -----------</p> <p>The BirdVox-70k dataset contains 70k half-second clips from 6 audio recordings in the BirdVox-full-night dataset, each about ten hours in duration. These recordings come from ROBIN autonomous recording units, placed near Ithaca, NY, USA during the fall 2015. They were captured on the night of September 23rd, 2015, by six different sensors, originally numbered 1, 2, 3, 5, 7, and 10.</p> <p>Andrew Farnsworth used the Raven software to pinpoint every avian flight call in time and frequency. He found 35402 flight calls in total. He estimates that about 25 different species of passerines (thrushes, warblers, and sparrows) are present in this recording. Species are not labeled in BirdVox-70k, but it is possible to tell apart thrushes from warblers and sparrrows by looking at the center frequencies of their calls. The annotation process took 102 hours.</p> <p>The dataset can be used, among other things, for the research,development and testing of bioacoustic classification mode ls, including the reproduction of the results reported in [1].</p> <p>For details on the hardware of ROBIN recording units, we refer the reader to [2].</p> <p>[1] V. Lostanlen, J. Salamon, A. Farnsworth, S. Kelling, J. Bello. BirdVox-full-night: a dataset and benchmark for avian flight call detection. Proc. IEEE ICASSP, 2018.</p> <p>[2] J. Salamon, J. P. Bello, A. Farnsworth, M. Robbins, S. Keen, H. Klinck, and S. Kelling. Towards the Automatic Classification of Avian Flight Calls for Bioacoustic Monitoring. PLoS One, 2016.</p> <p>@inproceedings{lostanlen2018icassp,<br> title = {BirdVox-full-night: a dataset and benchmark for avian flight call detection},<br> author = {Lostanlen, Vincent and Salamon, Justin and Farnsworth, Andrew and Kelling, Steve and Bello, Juan Pablo},<br> booktitle = {Proc. IEEE ICASSP},<br> year = {2018},<br> published = {IEEE},<br> venue = {Calgary, Canada},<br> month = {April},<br> }</p> <p> </p> <p>Data Files<br> ------------</p> <p>BirdVox-70k contains the recordings as HDF5 files, sampled at 24 kHz, with a single channel (mono). Each HDF5 file corresponds to a different sensor. The name of the HDF5 dataset in each file is "waveforms".</p> <p> </p> <p>Metadata Files<br> --------------</p> <p>Contrary to BirdVox-full-night, BirdVox-70k is not shipped with a metadata file. Rather, the metadata is included in the keys of the elements in the HDF5 files themselves, whose values are the waveforms.</p> <p>An example of BirdVox-70k key is:</p> <pre>unitID_TIMESTAMP_FREQ_LABEL </pre> <p>where</p> <ul> <li>ID is the identifier of the unit (01, 02, 03, 05, 07, or 10)</li> <li>TIMESTAMP is the timestamp of the center of the clip in the BirdVox-full-night recording. This timestamp is measured in samples at 24 kHz. It is accurate at about 10 ms.</li> <li>FREQ is the center frequency of the flight call, measured in Hertz. It is accurate at about 1 kHz. When the clip is negative, i.e. does not contain any flight call, it is set equal to zero by convention.</li> <li>LABEL is the label of the clip, positive (1) or negative (0).</li> </ul> <p> </p> <p>Example:</p> <pre>unit01_085256784_03636_1</pre> <p>is a positive clip in unit 01, with timestamp 085256784 (3552.37 seconds after dividing by the sample rate 24000), center frequency 3636 Hz.</p> <p> </p> <p>Another example:</p> <pre>unit05_284775340_00000_0</pre> <p>is a negative clip in unit 05, with timestamp 284775340 (11865.64 seconds).</p> <p> </p> <p>The approximate GPS coordinates of the sensors (latitudes and longitudes rounded to 2 decimal points) and UTC timestamps corresponding to the start of the recording for each sensor are included as CSV files in the main directory.</p> <p> </p> <p>Please acknowledge BirdVox-70k in academic research<br> ----------------------------------------------------------</p> <p>When BirdVox-70k is used for academic research, we would highly appreciate it if scientific publications of works partly based on this dataset cite the following publication:</p> <p>V. Lostanlen, J. Salamon, A. Farnsworth, S. Kelling, J. Bello. BirdVox-full-night: a dataset and benchmark for avian flight call detection, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2018.</p> <p>The creation of this dataset was supported by NSF grants 1125098 (BIRDCAST) and 1633259 (BIRDVOX), a Google Faculty Award, the Leon Levy Foundation, and two anonymous donors.</p> <p> </p> <p>Conditions of Use<br> -----------------</p> <p>Dataset created by Vincent Lostanlen, Justin Salamon, Andrew Farnsworth, Steve Kelling, and Juan Pablo Bello.</p> <p>The BirdVox-70k dataset is offered free of charge under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license:<br> https://creativecommons.org/licenses/by/4.0/</p> <p>The dataset and its contents are made available on an "as is" basis and without warranties of any kind, including without limitation satisfactory quality and conformity, merchantability, fitness for a particular purpose, accuracy or completeness, or absence of errors. Subject to any liability that may not be excluded or limited by law, Cornell Lab of Ornithology is not liable for, and expressly excludes all liability for, loss or damage however and whenever caused to anyone by any use of the BirdVox-70k dataset or any part of it.</p> <p> </p> <p>Feedback<br> -----------</p> <p>Please help us improve BirdVox-70k by sending your feedback to:<br> vincent.lostanlen@gmail.com and af27@cornell.edu</p> <p>In case of a problem, please include as many details as possible.</p> <p> </p> <p>Acknowledgements<br> ----------------</p> <p>Jessie Barry, Ian Davies, Tom Fredericks, Jeff Gerbracht, Sara Keen, Holger Klinck, Anne Klingensmith, Ray Mack, Peter Marchetto, Ed Moore, Matt Robbins, Ken Rosenberg, and Chris Tessaglia-Hymes.</p> <p>We acknowledge that the land on which the data was collected is the unceded territory of the Cayuga nation, which is part of the Haudenosaunee (Iroquois) confederacy.</p>
Peshawar, Pakistan. Mound of Shah ji ki Dheri, the so-called Kanishka reliquary.
<p>Peshawar, Pakistan. Mound of Shah ji ki Dheri, the so-called Kanishka reliquary, historic photograph with associated desposits.</p> <ul> </ul>
Training data for 'Somatic variant calling' tutorial (Galaxy Training Material)
<p>The data provided here are part of a Galaxy Training Network tutorial that demonstrates identification of somatic and germline variants from tumor and normal sample pairs.</p>
VCF File containing genotype calls for 136 Populus alba x Populus tremula hybrids obtained through both RAD-seq and GBS
<p>VCF file used to compare genotype calls obtained through RAD-seq and GBS for 126 common garden seedlings of Populus tremula and Populus alba hybrids. See Bresadola et al. (2019) for more details.</p>
Linux Kernel 4.21 Call Graphs
<p>This is the<strong> Linux Kernel 4.21 Call Graphs</strong> created using <a href="http://github.com/dspinellis/cscout">CScout</a> containing the following graphs:</p> <ol> <li>File include graph (fgraph_I.txt) </li> <li>Compile Time Dependency Graph (fgraph_C.txt)</li> <li>Control Dependency Graph (through function calls) (fgraph_F_D.txt)</li> <li>Data Dependency Graph (through global variables) (fgraph_G.txt)</li> <li>Function and Macro Call Graph (cgraph.txt)</li> </ol> <p>Files are of the form</p> <p>foo.c boo.c</p> <p>which indicate a directed edge foo.c -> boo.c.</p> <p>The call graphs refer to <strong>all </strong>(ending with _all.txt) files or only the <strong>writable files.</strong> </p> <p>These graphs were produced by processing the Linux Kernel Codebase consisting of 20.3 million lines of source code. </p> <p>The results were produced on an Intel(R) Xeon(R) CPU E5-1410 0 @ 2.80GHz server with 64GB of RAM.</p> <p><strong>References: </strong></p> <p>1. Papachristou, Marios. "Software clusterings with vector semantics and the call graph." <em>Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering</em>. 2019.</p>
SNP call data for: The current epidemic of the barley pathogen Ramularia collo-cygni derives from a recent population expansion and shows global admixture
<p>Ramularia Leaf Spot is becoming an ever increasing problem in main barley growing regions since the 1980s, causing up to 70% yield loss in extreme cases. Yet, the causal agent <em>Ramularia collo-cygni</em>, remains poorly studied. The diversity of the pathogen in the field thus far remains unknown. Furthermore, it is unknown to which extend the pathogen has a sexual reproductive cycle. To date, the teleomorph of <em>R. collo-cygni</em> has not been observed.</p> <p>To study the genetic diversity of <em>R. collo-cygni </em>and to get more insights into its biology, we sequenced the genomes of 19 <em>R. collo-cygn</em>i isolates from multiple geographic locations and diverse hosts. Here we share the SNP call data as well as the reference genome.</p> <p>The reference genome files and assembly can be found on ENI: GCA_900074925.1</p> <p>https://www.ebi.ac.uk/ena/data/view/GCA_900074925.1</p> <p>The raw sequence data is also available through ENI: ERX2296228</p> <p>https://www.ebi.ac.uk/ena/data/view/ERX2296228</p>
BirdVox-scaper-10k: a synthetic dataset for multilabel species classification of flight calls from 10-second audio recordings
<p>BirdVox-scaper-10k: a synthetic dataset for multilabel species classification of flight calls from 10-second audio recordings<br> =============================================================================================<br> Version 1.0, September 2019.</p> <p> </p> <p>Created By<br> -------------</p> <p>Elizabeth Mendoza (1), Vincent Lostanlen (2, 3, 4), Justin Salamon (3, 4), Andrew Farnsworth (2), Steve Kelling (2), and Juan Pablo Bello (3, 4).</p> <p> </p> <p>(1): Forest Hills High School, New York, NY, USA<br> (2): Cornell Lab of Ornithology, Cornell University, Ithaca, NY, USA<br> (3): Center for Urban Science and Progress, New York University, New York, NY, USA<br> (4): Music and Audio Research Lab, New York University, New York, NY, USA</p> <p>https://wp.nyu.edu/birdvox</p> <p> </p> <p>Description<br> --------------</p> <p>The BirdVox-scaper-10k dataset contains 9983 artificial soundscapes. Each soundscape lasts exactly ten seconds and contains one or several avian flight calls from up to 30 different species of New World warblers (Parulidae). Alongside each audio file, we include an annotation file describing the start time and end time of each flight call in the corresponding soundscape, as well as the species of warbler it belongs to.</p> <p>In order to synthesize soundscapes in BirdVox-scaper-10k, we mixed natural sounds from various pre-recorded sources. First, we extracted isolated recordings of flight calls containing little or no background noise from the CLO-43SD dataset [1]. Secondly, we extracted 10-second "empty" acoustic scenes from the BirdVox-DCASE-20k dataset [2]. These acoustic scenes contain various sources of real-world background noise, including biophony (insects) and anthropophony (vehicles), yet are guaranteed to be devoid of any flight calls. Lastly, we "fill" each acoustic scene by mixing it with flight calls sampled at random.</p> <p>Although the BirdVox-scaper-10k does not consist of natural recordings, we have taken several measures to ensure the plausibility of each synthesized soundscape, both from qualitative and quantitative standpoints.<br> <br> The BirdVox-scaper-10k dataset can be used, among other things, for the research, development, and testing of bioacoustic classification models.</p> <p>For details on the hardware of ROBIN recording units, we refer the reader to [2].</p> <p>[1] J. Salamon, J. Bello. Fusing shallow and deep learning for bioacoustic bird species classification. Proc. IEEE ICASSP, 2017.</p> <p>[2] V. Lostanlen, J. Salamon, A. Farnsworth, S. Kelling, and J. Bello. BirdVox-full-night: a dataset and benchmark for avian flight call detection. Proc. IEEE ICASSP, 2018.</p> <p>[3] J. Salamon, J. P. Bello, A. Farnsworth, M. Robbins, S. Keen, H. Klinck, and S. Kelling. Towards the Automatic Classification of Avian Flight Calls for Bioacoustic Monitoring. PLoS One, 2016.</p> <p> </p> <p> </p> <p> </p> <p>@inproceedings{lostanlen2018icassp,<br> title = {BirdVox-full-night: a dataset and benchmark for avian flight call detection},<br> author = {Lostanlen, Vincent and Salamon, Justin and Farnsworth, Andrew and Kelling, Steve and Bello, Juan Pablo},<br> booktitle = {Proc. IEEE ICASSP},<br> year = {2018},<br> published = {IEEE},<br> venue = {Calgary, Canada},<br> month = {April},<br> }</p>
Implementation of Genomic Variant Calling Using GATK4, SPARK, WDL, CROMWELL and DOCKER Over Simulated Ebola NGS Dataset.
<p>Ebola genome is manually mutated to contain non-structural as well as structural variants. One ebola genome contains non-structural variants - 10 SNPs, 10 INDELs, 05 TRANSLOCATIONs, 05 INSERSIONs and their reverse complements. Similarly, other two set of mutated genomes contain structural variants. Each set contains seven mutated ebola genome each one for large deletion, insertion, duplication, translocation, inversion, complex variant1 (consecutive three mutations - insertion, duplication and deletion) and complex variants2 (consecutive three mutations - deletion, duplication and deletion). All insertions are novel sequence insertion.</p> <p> </p>
Baboon and Gelada SNP Calls VCF
<p>Bgzipped vcf and tabix index files of baboon and gelada SNP calls of 16 individuals on the papAnu2 assembly as published in Rogers et al. (2019). The comparative genomics and complex population history of Papio baboons. Science Advances. 30 Jan 2019: Vol. 5, no. 1, eaau6947 DOI: 10.1126/sciadv.aau6947.</p>
Figure 2 in A call for collaboration to create the European Atlas of Soil Fauna
Figure 2. Example map created from the data stored in the Edaphobase data warehouse. The yellow triangles depict the distribution of the Diplopod genera Glomeris (A) and Geoglomeris (B). Please note that the absence of points does not necessarily mean that the genus is absent, but rather means that the genus has either not been recorded (yet) or it has been recorded but relevant data have not been included in the Edaphobase data warehouse.
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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.