cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.60mm2
title: Data from: Convergence of ion channel genome content in early animal evolution

description: Multicellularity has evolved multiple times, but animals are the only
 multicellular lineage with nervous systems. This fact implies that the
 origin of nervous systems was an unlikely event, yet recent comparisons
 among extant taxa suggest that animal nervous systems may have evolved
 multiple times independently. Here, we use ancestral gene content
 reconstruction to track the timing of gene family expansions for the major
 families of ion-channel proteins that drive nervous system function. We
 find that animals with nervous systems have broadly similar complements of
 ion-channel types but that these complements likely evolved independently.
 We also find that ion-channel gene family evolution has included large
 loss events, two of which were immediately followed by rounds of
 duplication. Ctenophores, cnidarians, and bilaterians underwent
 independent bouts of gene expansion in channel families involved in
 synaptic transmission and action potential shaping. We suggest that
 expansions of these family types may represent a genomic signature of
 expanding nervous system complexity. Ancestral nodes in which nervous
 systems are currently hypothesized to have originated did not experience
 large expansions, making it difficult to distinguish among competing
 hypotheses of nervous system origins and suggesting that the origin of
 nerves was not attended by an immediate burst of complexity. Rather, the
 evolution of nervous system complexity appears to resemble a slow fuse in
 stem animals followed by many independent bouts of gene gain and loss.
description: Liebeskind2015PNAS.tarSequences, alignments, trees, and other data used in ancestral genome content analysis.
DOI: 10.5061/dryad.7p60n
title: Data from: Space-use behavior of woodland caribou based on a cognitive movement model

description: 1. Movement patterns offer a rich source of information on animal
 behaviour and the ecological significance of landscape attributes. This is
 especially useful for species occupying remote landscapes where direct
 behavioural observations are limited. In this study, we fit a mechanistic
 model of animal cognition and movement to GPS positional data of woodland
 caribou (Rangifer tarandus caribou; Gmelin 1788) collected over a wide
 range of ecological conditions. 2. The model explicitly tracks individual
 animal informational state over space and time, with resulting parameter
 estimates that have direct cognitive and ecological meaning. Three biotic
 landscape attributes were hypothesized to motivate caribou movement:
 forage abundance (dietary digestible biomass), wolf (Canis lupus;
 Linnaeus, 1758) density and moose (Alces alces; Linnaeus, 1758) habitat.
 Wolves are the main predator of caribou in this system and moose are their
 primary prey. 3. Resulting parameter estimates clearly indicated that
 forage abundance is an important driver of caribou movement patterns, with
 predator and moose avoidance often having a strong effect, but not for all
 individuals. From the cognitive perspective, our results support the
 notion that caribou rely on limited sensory inputs from their
 surroundings, as well as on long-term spatial memory, to make informed
 movement decisions. Our study demonstrates how sensory, memory and motion
 capacities may interact with ecological fitness covariates to influence
 movement decisions by free-ranging animals.
description: data_2.313_5a .mat file containing all data needed to run the cognitive movement model for a single animal: AU313
DOI: 10.5061/dryad.ds68k
title: Data from: Metabolic cross-feeding via intercellular nanotubes among bacteria

description: Bacteria frequently exchange metabolites by diffusion through the
 extracellular environment, yet it remains generally unclear whether
 bacteria can also use cell–cell connections to directly exchange
 nutrients. Here we address this question by engineering cross-feeding
 interactions within and between Acinetobacter baylyi and Escherichia coli,
 in which two distant bacterial species reciprocally exchange essential
 amino acids. We establish that in a well-mixed environment E. coli, but
 likely not A. baylyi, can connect to other bacterial cells via
 membrane-derived nanotubes and use these to exchange cytoplasmic
 constituents. Intercellular connections are induced by auxotrophy-causing
 mutations and cease to establish when amino acids are externally supplied.
 Electron and fluorescence microscopy reveal a network of nanotubular
 structures that connects bacterial cells and enables an intercellular
 transfer of cytoplasmic materials. Together, our results demonstrate that
 bacteria can use nanotubes to exchange nutrients among connected cells and
 thus help to distribute metabolic functions within microbial communities.
description: Timelapse images showing
 transfer of GFP between cellsCo-cultures of
 cross-feeding genotypes of E.coli and A.baylyi were observed after 9 hours
 of growth in liquid media. Images of this co-culture were taken every 2
 minutes to visualize the transfer of GFP between cells connected by
 nanotubes. The zip file contains unprocessed images in tiff format of
 three different channels- bright-field, green and red. Each folder
 contains 18 images, the file name indicates the time
 point.tiff_images_all_timepoints.zip
DOI: 10.5061/dryad.fq268
title: Data from: Large regional differences in incidence of arthroscopic meniscal procedures in the public and private sector in Denmark

description: Objectives: A recent study reported a large increase in the number of
 meniscal procedures from 2000 to 2011 in Denmark. We examined the
 nation-wide distribution of meniscal procedures performed in the private
 and public sector in Denmark since different incentives may be present and
 the use of these procedures may differ from region to region. Setting: We
 included data on all patients who underwent an arthroscopic meniscal
 procedure performed in the public or private sector in Denmark.
 Participants: Data were retrieved from the Danish National Patient
 Register on patients who underwent arthroscopic meniscus surgery as a
 primary or secondary procedure in the years 2000 to 2011. Hospital
 identification codes enabled linkage of performed procedures to specific
 hospitals. Primary and secondary outcome measures: Yearly incidence of
 meniscal procedures per 100 000 inhabitants was calculated with 95% CIs
 for public and private procedures for each region. Results: Incidence of
 meniscal procedures increased at private and at public hospitals. The
 private sector accounted for the largest relative and absolute increase,
 rising from an incidence of 1 in 2000 to 98 in 2011. In 2011, the
 incidence of meniscal procedures was three times higher in the Capital
 Region than in Region Zealand. Conclusions: Our study identified a large
 increase in the use of meniscal procedures in the public and private
 sector in Denmark. The increase was particularly conspicuous in the
 private sector as its proportion of procedures performed increased from 1%
 to 32%. Substantial regional differences were present in the incidence and
 trend over time of meniscal procedures.
description: Procedures per year
 divided on region and public or private hospitalProcedures.xlsx
DOI: 10.5061/dryad.7891
title: Data from: Time-dependent speciation and extinction from phylogenies: a least squares approach

description: Molecular phylogenies contribute to the study of the patterns and
 processes of macroevolution even though past events (fossils) are not
 recorded in these data. In this paper, I consider the general
 time-dependent birth–death model in order to fit any model of temporal
 variation in speciation and extinction to phylogenies. I establish
 formulae to compute the expected cumulative distribution function of
 branching times for any model, and, building on previous published works,
 I derive maximum likelihood estimators. Some limitations of the likelihood
 approach are described, and a fitting procedure based on least squares is
 developed that alleviates the shortcomings of maximum likelihood in the
 present context. Parametric and nonparametric bootstrap procedures are
 developed to assess uncertainty in the parameter estimates, the latter
 version giving narrower confidence intervals and being faster to compute.
 I also present several general algorithms of tree simulation in continuous
 time. I illustrate the application of this approach with the analysis of
 simulated data sets, and two published phylogenies of primates
 (Catarrhinae) and lizards (Agamidae).
description: constant-rate-treethe phylogeny on Fig. 4Athousand-constant-rate-trees.tre1000 phylogenies simulated with the same parameters than the above one (the Newick file was compressed with gzip)logistic-rates-treethe phylogeny on Fig. 5Athousand-logistic-rates-trees.tre1000 phylogenies simulated with the same parameters than the above one (the Newick file was compressed with gzip)agamidsthe agamid phylogenyCatarrhinithe catarrhine phylogeny
DOI: 10.5061/dryad.r0005
title: Data from: Crowdsourcing the identification of organisms: a case-study of iSpot

description: Accurate species identification is fundamental to biodiversity science,
 but the natural history skills required for this are neglected in formal
 education at all levels. In this paper we describe how the web application
 ispotnature.org and its sister site ispot.org.za (collectively,
 "iSpot") are helping to solve this problem by combining learning
 technology with crowdsourcing to connect beginners with experts. Over 94%
 of observations submitted to iSpot receive a determination. To date
 (2014), iSpot has crowdsourced the identification of 30,000 taxa
 (&gt;80% at species level) in &gt; 390,000 observations with a
 global community numbering &gt; 42,000 registered participants. More
 than half the observations on ispotnature.org were named within an hour of
 submission. iSpot uses a unique, 9-dimensional reputation system to
 motivate and reward participants and to verify determinations.
 Taxon-specific reputation points are earned when a parti! cipant proposes
 an identification that achieves agreement from other participants,
 weighted by the agreers' own reputation scores for the taxon. This
 system is able to discriminate effectively between competing
 determinations when two or more are proposed for the same observation. In
 57% of such cases the reputation system improved the accuracy of the
 determination, while in the remainder it either improved precision (e.g.
 by adding a species name to a genus) or revealed false precision, for
 example where a determination to species level was not supported by the
 available evidence. We propose that the success of iSpot arises from the
 structure of its social network which efficiently connects beginners and
 experts, overcoming the social as well as geographic barriers that
 normally separate the two.
description: Excel tables of data
 used in analyses and plotsA zip file of 5 excel
 workbooks.Data for
 deposit.zip
DOI: 10.5061/dryad.n21cr
title: Data from: Parallel tagged amplicon sequencing of relatively long PCR products using the Illumina HiSeq platform and transcriptome assembly

description: In phylogenetics and population genetics, a large number of loci are often
 needed to accurately resolve species relationships. Normally, loci are
 enriched by PCR and sequenced by Sanger sequencing, which is expensive
 when the number of amplicons is large. Next-generation sequencing (NGS)
 techniques are increasingly used for parallel amplicon sequencing, which
 reduces sequencing costs tremendously, but has not reduced preparation
 costs very much. Moreover, for most current NGS methods, amplicons need to
 be purified and quantified before sequencing and their lengths are also
 restricted (normally &lt; 700 bp). Here, we describe an approach to
 sequence pooled amplicons of any length using the Illumina platform. Using
 this method, amplicons are pooled at equal volume rather than at equal
 concentration, thus eliminating the laborious purification and
 quantification steps. We then shear the pooled amplicons, repair the ends,
 add sample identifying linkers, and pool multiple samples prior to
 Illumina library preparation. Data are then assembled using the
 transcriptome assembly program Trinity, which is optimized to deal with
 templates of highly varying quantities. We demonstrated the utility of our
 approach by recovering 93.5% of the target amplicons (size up to 1650 bp)
 in full length for a 16 taxa × 101 loci project, using ~2.0 GB of Illumina
 HiSeq paired-end 90 bp data. Overall, we validate a rapid, cost-effective
 and scalable approach to sequence a large number of targeted loci from a
 large number of samples that is particularly suitable for both
 phylogenetics and population genetics studies that require a modest scale
 of data.
description: Python
 ScriptThis file contains the
 python scripts used in this study. These scripts can be used to analysis
 next generation sequence data step by step, including: sorting,
 assembling, trimming, refining and combining.Total_1435_consensus_seqsThis is the final consensus sequences produced by our approach. These data can be used for phylogenetic analysis.Alignment_for_RAxMLThis alignment is used for ML analysis.Alignment_for_MrbayesThis alignment is used for Mrbayes analysis. The parameters are also included in this file.16taxa_species_treeThis is the species tree result.16_taxa_raxm_&bayes_treeThis tree file contains the results from RAxML and Mrbayes. Both methods result the same topologies and same support values.
DOI: 10.15468/dl.wvuz4u
title: Occurrence Download

description: A dataset containing 442 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Hordeum vulgare",
 "Year 1970-2000"
 ]
}

 The dataset includes 442 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006285-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dvzz28
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((89.1768 23.977848, 89.099947 23.972271, 89.02500499999999 23.955679, 88.953838 23.928485, 88.888211 23.891363, 88.82974900000001 23.845237, 88.779894 23.791251, 88.73987099999999 23.730743, 88.710656 23.66521, 88.692955 23.596272, 88.687185 23.52563, 88.693471 23.455026, 88.71163799999999 23.386195, 88.74122199999999 23.320829, 88.781482 23.260532, 88.831419 23.20678, 88.889799 23.160887, 88.955189 23.123977, 89.025987 23.09695, 89.100463 23.080465, 89.1768 23.074926, 89.253137 23.080465, 89.327613 23.09695, 89.398411 23.123977, 89.463801 23.160887, 89.522181 23.20678, 89.572118 23.260532, 89.61237800000001 23.320829, 89.64196200000001 23.386195, 89.660129 23.455026, 89.666415 23.52563, 89.660645 23.596272, 89.642944 23.66521, 89.61372900000001 23.730743, 89.573706 23.791251, 89.52385099999999 23.845237, 89.465389 23.891363, 89.399762 23.928485, 89.32859500000001 23.955679, 89.253653 23.972271, 89.1768 23.977848))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006286-260120142942310/datasets/export for details.
DOI: 10.6084/m9.figshare.31131808
title: Dataset for CAMEX

description: Data for: <br>Muti-species integration, alignment and annotation of single-cell RNA-seq data with CAMEX<br>Abstract: <br>Single-cell RNA-seq (scRNA-seq) data from multiple species present remarkable opportunities to explore cellular origins and evolution. However, integrating and annotating scRNA-seq data across different species remains challenging due to the variations in sequencing techniques, ambiguity of homologous relationships, and limited biological knowledge. To tackle the above challenges, we introduce CAMEX, a heterogeneous Graph Neural Network (GNN) tool that leverages many-to-many homologous relationships for multi-species integration, alignment, and annotation of scRNA-seq data from multiple species. Notably, CAMEX outperforms state-of-the-art methods integration on various cross-species benchmarking datasets (ranging from one to eleven species). Besides, CAMEX facilitates the alignment of diverse species across different developmental stages, significantly enhancing our understanding of organ and organism origins. Furthermore, CAMEX enables the detection of species-specific cell types and marker genes through cell and gene embedding. In short, CAMEX holds the potential to provide invaluable insights into how evolutionary forces operate across different species at single-cell resolution.
DOI: 10.6084/m9.figshare.31131808.v1
title: Dataset for CAMEX

description: Data for: <br>Muti-species integration, alignment and annotation of single-cell RNA-seq data with CAMEX<br>Abstract: <br>Single-cell RNA-seq (scRNA-seq) data from multiple species present remarkable opportunities to explore cellular origins and evolution. However, integrating and annotating scRNA-seq data across different species remains challenging due to the variations in sequencing techniques, ambiguity of homologous relationships, and limited biological knowledge. To tackle the above challenges, we introduce CAMEX, a heterogeneous Graph Neural Network (GNN) tool that leverages many-to-many homologous relationships for multi-species integration, alignment, and annotation of scRNA-seq data from multiple species. Notably, CAMEX outperforms state-of-the-art methods integration on various cross-species benchmarking datasets (ranging from one to eleven species). Besides, CAMEX facilitates the alignment of diverse species across different developmental stages, significantly enhancing our understanding of organ and organism origins. Furthermore, CAMEX enables the detection of species-specific cell types and marker genes through cell and gene embedding. In short, CAMEX holds the potential to provide invaluable insights into how evolutionary forces operate across different species at single-cell resolution.
DOI: 10.15468/dl.m9wtrj
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((89.1267 23.999547, 89.049834 23.99397, 88.974879 23.977378, 88.9037 23.950183, 88.83806199999999 23.913062, 88.779591 23.866936, 88.72972799999999 23.81295, 88.689699 23.752441, 88.660479 23.686908, 88.642775 23.617971, 88.637005 23.547329, 88.643292 23.476725, 88.661462 23.407895, 88.691051 23.342529, 88.731318 23.282232, 88.781263 23.22848, 88.839653 23.182588, 88.905053 23.145678, 88.97586200000001 23.118651, 89.05034999999999 23.102167, 89.1267 23.096627, 89.20305 23.102167, 89.27753800000001 23.118651, 89.348347 23.145678, 89.413747 23.182588, 89.472137 23.22848, 89.522082 23.282232, 89.562349 23.342529, 89.591938 23.407895, 89.610108 23.476725, 89.616395 23.547329, 89.610625 23.617971, 89.592921 23.686908, 89.56370099999999 23.752441, 89.523672 23.81295, 89.473809 23.866936, 89.41533800000001 23.913062, 89.3497 23.950183, 89.278521 23.977378, 89.203566 23.99397, 89.1267 23.999547))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006289-260120142942310/datasets/export for details.
DOI: 10.5281/zenodo.18324207
title: TAPS: Throat and Acoustic Paired Speech Dataset (Korean)

description: TAPS (Throat and Acoustic Paired Speech) is a paired speech corpus for deep learning–based speech enhancement, providing synchronized recordings from an accelerometer-based throat microphone and an acoustic microphone.

 

Contents:- 60 native Korean speakers, gender-balanced (50/50)- Total: 6,000 utterances, ~15.3 hours- Splits: train (4,000 utt, 40 speakers), dev (1,000 utt, 10 speakers), test (1,000 utt, 10 speakers)- No speaker overlap across splits

 

Files:This Zenodo record contains ZIP archives for each split. The training split is provided as four ZIP files due to upload size constraints:- TAPS_data_train_1.zip- TAPS_data_train_2.zip- TAPS_data_train_3.zip- TAPS_data_train_4.zip- TAPS_data_dev.zip- TAPS_data_test.zip

To use the full training set, download and extract all four training ZIP files into the same target directory.

 

Inside each ZIP:<split>/<speaker_id>/<sentence_id>/- throat_microphone.wav (paired throat signal)- acoustic_microphone.wav (paired acoustic signal)- features.json (metadata)

 

Metadata fields (features.json):- gender, speaker_id, sentence_id, duration- text: original transcription- normalized_text: normalized transcription (numbers spelled out in Korean; punctuation normalized)- throat_microphone/acoustic_microphone: sampling_rate, num_samples, etc.

 

Use cases:- throat-microphone speech enhancement (recovering attenuated high-frequency components)- multimodal speech processing and related tasks

 

Project homepage and an alternative distribution (different file format) are provided in Related works. The accompanying paper is available on arXiv.
DOI: 10.5281/zenodo.18324208
title: TAPS: Throat and Acoustic Paired Speech Dataset (Korean)

description: TAPS (Throat and Acoustic Paired Speech) is a paired speech corpus for deep learning–based speech enhancement, providing synchronized recordings from an accelerometer-based throat microphone and an acoustic microphone.

 

Contents:- 60 native Korean speakers, gender-balanced (50/50)- Total: 6,000 utterances, ~15.3 hours- Splits: train (4,000 utt, 40 speakers), dev (1,000 utt, 10 speakers), test (1,000 utt, 10 speakers)- No speaker overlap across splits

 

Files:This Zenodo record contains ZIP archives for each split. The training split is provided as four ZIP files due to upload size constraints:- TAPS_data_train_1.zip- TAPS_data_train_2.zip- TAPS_data_train_3.zip- TAPS_data_train_4.zip- TAPS_data_dev.zip- TAPS_data_test.zip

To use the full training set, download and extract all four training ZIP files into the same target directory.

 

Inside each ZIP:<split>/<speaker_id>/<sentence_id>/- throat_microphone.wav (paired throat signal)- acoustic_microphone.wav (paired acoustic signal)- features.json (metadata)

 

Metadata fields (features.json):- gender, speaker_id, sentence_id, duration- text: original transcription- normalized_text: normalized transcription (numbers spelled out in Korean; punctuation normalized)- throat_microphone/acoustic_microphone: sampling_rate, num_samples, etc.

 

Use cases:- throat-microphone speech enhancement (recovering attenuated high-frequency components)- multimodal speech processing and related tasks

 

Project homepage and an alternative distribution (different file format) are provided in Related works. The accompanying paper is available on arXiv.