cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/102279
title: A Virtual Library for Behavioral Performance in Standard Conditions – Experiment 08 Q26 Effect of an NMDA lesion of the NAc on the expression of sensitization and compulsive checking

description: Beyond their specific experiment, video records of behavior have future value; for example, as inputs for new experiments or for yet unknown types of analysis of behaviorsimilar to tissue or blood sample banks in life sciences where clinically-derived or otherwise well-described experimental samples are stored to be available for some unknown potential future purpose. <br>Research using an animal model of obsessive-compulsive disorder employed a standardized paradigm where the behavior of rats in a large open field was video recorded for 55 min on each test. From 43 experiments, there are 19,976 such trials that amount to over 2 years of continuous recording. In addition to videos, there are two video-derived raw data objects: XY locomotion coordinates, and plots of animal trajectory. To motivate future use, the three raw data objects are annotated with a general schemaone that abstracts the data records from their particular experiment while providing, at the same time a detailed list of independent variables bearing on behavioral performance. The raw data objects are deposited as 43 datasets but constitute, functionally, a library containing one large dataset. <br>Size and annotation schema give the library high re-use potential: in applications using machine learning techniques, statistical evaluation of subtle factors, simulation of new experiments, or as educational resource. Ultimately, the library can serve both as the seed and the test bed to create a machine searchable virtual library of linked open datasets for behavioral performance in defined conditions.
DOI: 10.5524/102280
title: A Virtual Library for Behavioral Performance in Standard Conditions – Experiment 09 Q23 Effect of co-treatment with kappa agonist U69593 and QNP on the development of sensitization and compulsive checking

description: Beyond their specific experiment, video records of behavior have future value; for example, as inputs for new experiments or for yet unknown types of analysis of behaviorsimilar to tissue or blood sample banks in life sciences where clinically-derived or otherwise well-described experimental samples are stored to be available for some unknown potential future purpose. <br>Research using an animal model of obsessive-compulsive disorder employed a standardized paradigm where the behavior of rats in a large open field was video recorded for 55 min on each test. From 43 experiments, there are 19,976 such trials that amount to over 2 years of continuous recording. In addition to videos, there are two video-derived raw data objects: XY locomotion coordinates, and plots of animal trajectory. To motivate future use, the three raw data objects are annotated with a general schemaone that abstracts the data records from their particular experiment while providing, at the same time a detailed list of independent variables bearing on behavioral performance. The raw data objects are deposited as 43 datasets but constitute, functionally, a library containing one large dataset. <br>Size and annotation schema give the library high re-use potential: in applications using machine learning techniques, statistical evaluation of subtle factors, simulation of new experiments, or as educational resource. Ultimately, the library can serve both as the seed and the test bed to create a machine searchable virtual library of linked open datasets for behavioral performance in defined conditions.
DOI: 10.5524/102283
title: A Virtual Library for Behavioral Performance in Standard Conditions – Experiment 12 Q34 Comparison of the QNP (0.2 mg/kg) and the 8OHDPAT (1 mg/kg) effects on the development of sensitization and compulsive checking

description: Beyond their specific experiment, video records of behavior have future value; for example, as inputs for new experiments or for yet unknown types of analysis of behaviorsimilar to tissue or blood sample banks in life sciences where clinically-derived or otherwise well-described experimental samples are stored to be available for some unknown potential future purpose. <br>Research using an animal model of obsessive-compulsive disorder employed a standardized paradigm where the behavior of rats in a large open field was video recorded for 55 min on each test. From 43 experiments, there are 19,976 such trials that amount to over 2 years of continuous recording. In addition to videos, there are two video-derived raw data objects: XY locomotion coordinates, and plots of animal trajectory. To motivate future use, the three raw data objects are annotated with a general schemaone that abstracts the data records from their particular experiment while providing, at the same time a detailed list of independent variables bearing on behavioral performance. The raw data objects are deposited as 43 datasets but constitute, functionally, a library containing one large dataset. <br>Size and annotation schema give the library high re-use potential: in applications using machine learning techniques, statistical evaluation of subtle factors, simulation of new experiments, or as educational resource. Ultimately, the library can serve both as the seed and the test bed to create a machine searchable virtual library of linked open datasets for behavioral performance in defined conditions.
DOI: 10.5281/zenodo.5711932
title: Quantifying research interests in 7,521 mammalian species with h-index: a case study (scopus output)

description: Dataset of bibliometric data collected from Scopus for the manuscript 'Quantifying research interests in 7,521 mammalian species with h-index: a case study'.
DOI: 10.5281/zenodo.6644032
title: Quantifying research interests in 7,521 mammalian species with h-index: a case study (model output)

description: Model results for Quantifying research interests in 7,521 mammalian species with h-index: a case study
DOI: 10.5524/102236
title: Supporting data for "Meta-Prism 2.0: Enabling algorithm and web server for ultra-fast, memory-efficient, and accurate analysis among millions of microbial community samples"

description: Microbial community samples have been accumulated at a speed faster than ever, with hundreds of thousands of samples been sequenced each year. Mining such a huge amount of multi-source heterogeneous data is becoming an increasingly difficult challenge, so efficient and accurate compare and search of samples are in urgent need: Faced with millions of samples in the data repository, traditional sample comparison and search approaches fall short in speed and accuracy. <br> Here we proposed Meta-Prism 2.0, a microbial community sample analysis method that has pushed the time and memory efficiency to a new limit without compromising accuracy. Based on sparse data structure, time-saving instruction pipeline, and SIMD optimization, Meta-Prism 2.0 has enabled ultra-fast, memory-efficient, flexible and accurate search among millions of samples. Meta-Prism 2.0 was put to test on several datasets, with the largest containing one million samples. Results show that Meta-Prism 2.0s 0.00001s per sample pair compare speed and 8GB memory needs for searching against one million samples have made it one of the most efficient sample analysis methods. Additionally, Meta-Prism 2.0 can achieve accuracy comparable with or better than other contemporary methods. Thirdly, Meta-Prism 2.0 can precisely identify the original biome for samples, thus enabling sample source tracking. Finally, we have provided a web server for fast search of microbial community samples online.<br> In summary, Meta-Prism 2.0 has changed the resource-intensive sample search scheme to an effective procedure, which could be conducted by researchers every day even on a laptop, for insightful sample search, similarity analysis and knowledge discovery. Meta-Prism 2.0 can be accessed in GitHub, and the web server can be accessed here.
DOI: 10.5524/102237
title: Supporting data for "Quantifying research interests in 7,521 mammalian species with <i>h</i>-index: a case study"

description: Taxonomic bias is a known issue within the field of biology, causing scientific knowledge to be unevenly distributed across species. However, a systematic quantification of the research interest that the scientific community has allocated to individual species remains a big data problem. Scalable approaches are needed to integrate biodiversity datasets and bibliometric methods across large numbers of species. The outputs of these analyses are important for identifying understudied species and directing future research to fill these gaps. <br>In this study, we used the species <i>h</i>-index to quantify the research interest in 7,521 species of mammals. We tested factors potentially driving species <i>h</i>-index, by using a Bayesian phylogenetic generalised linear mixed model (GLMM). We found that a third of the mammals had a species <i>h</i>-index of zero, while a select few had inflated research interest. Further, mammals with higher species <i>h</i>-index had larger body masses, were found in temperate latitudes, had more humans uses, including domestication, and were in lower risk IUCN Red List categories. These results surprisingly suggested that critically endangered mammals are understudied. A higher interest in domesticated species suggested that human use rather than conservation drives mammalian scientific literature. <br>Our study has demonstrated a scalable workflow and systematically identified understudied species of mammals, as well as identified the likely drivers of this taxonomic bias in the literature. This case study can become a benchmark for future research that asks similar biological and meta-research questions for other taxa.
DOI: 10.5524/102239
title: Supporting data for "First de novo whole genome sequencing and assembly of mutant Dendrobium hybrid cultivar Emma White"

description: <i>Dendrobium</i> hybrid cultivar Emma White is an ornamental orchid with high commercial demand. We have used gamma-ray induced early flowering mutant to generate draft genome sequences with total length of 678,650,699 bp (longest contig 447,500 bp) with N50 of 1,423 bp using the Illumina HiSeqX10 sequencing platform. Here, we report first <i>de novo</i> whole genome sequencing and assembly of an early flowering gamma mutant of Emma White hybrid for developing a genomics resource for further studies. The GC content of genome was 33.48%, and predicted 95,529 genes from contig assembly. The predicted genes from the MaSuRCA (version 4.0.3) assembled contigs, when compared with UniProt database using BLASTX program with e-value cutoff of 0.001 resulted in 60,741 potential genes governing different pathways in terms for molecular functions, biological process and cellular components. We also identified 216,232 SSRs and 138,856 microsatellite markers.<br>Chromosome level genome assembly of <i>Dendrobium huoshanense</i> species was used to RagTag scaffold the available contigs of mutant, where it contained total length of 687,254,899 bp with N50 value 2,096. The final contig lengths ranged from 30,571 bp to 18,000,059 bp. The genome completeness for Emma White RagTag scaffold assembly was assessed to be 93.6% using BUSCO v5.2.1 against the Viridiplantae odb10 orthologous dataset. <i>De novo</i> whole genome sequencing of gamma mutant <i>Dendrobium</i> hybrid cultivar Emma White (10Gy) isolate was deposited to National Centre for Biotechnology Information (NCBI) with SRA accession SRR16008784, Genebank assembly accession GCA_021234465.1 under BioProject ID PRJNA763052. This study could provide valuable information for investigating the potential mechanisms of mutation, and guidance for developing <i>Dendrobium</i> hybrid cultivars using mutation breeding.
DOI: 10.5524/102240
title: Supporting data for "DeePVP: Identification and classification of phage virion proteins using deep learning"

description: Many biological properties of phages are determined by phage virion proteins (PVPs), and the poor annotation of PVPs is a bottleneck for many areas of viral research, such as viral phylogenetic analysis, viral host identification and antibacterial drug design. Because of the high diversity of PVP sequences, the PVP annotation of a phage genome remains a particularly challenging bioinformatic task.<br>Based on deep learning, we developed DeePVP. The main module of DeePVP aims to discriminate PVPs from non-PVPs within a phage genome, while the extended module of DeePVP can further classify predicted PVPs into the ten major classes of PVPs. Compared with the present state-of-the-art tools, the main module of DeePVP performs better, with a 9.05% higher <i>F1-score</i> in the PVP identification task. Moreover, the overall <i>accuracy</i> of the extended module of DeePVP in the PVP classification task is approximately 3.72% higher than that of PhANNs. Two application cases show that the predictions of DeePVP are more reliable and can better reveal the compact PVP-enriched region than the current state-of-the-art tools. Particularly, in the <i>Escherichia</i> phage phiEC1 genome, a novel PVP-enriched region that is conserved in many other <i>Escherichia</i> phage genomes was identified, indicating that DeePVP will be a useful tool for the analysis of phage genomic structures. <br>DeePVP outperforms state-of-the-art tools. The program is optimized in both a virtual machine with GUI and a docker so that the tool can be easily run by non-computer professionals.
DOI: 10.5524/102241
title: Supporting data for "The complexity landscape of viral genomes"

description: Viruses are amongst the shortest yet highly abundant species that harbor minimal instructions to infect cells, adapt, multiply, and exist. With the current substantial availability of viral genome sequences, the scientific repertory lacks a complexity landscape that automatically enlights viral genomes organization, relation, and fundamental characteristics.<br>This work provides a comprehensive landscape of the viral genomes complexity (or quantity of information),identifying the most redundant and complex groups regarding their genome sequence while providing their distribution and characteristics at a large and local scale. For this purpose, we measure the sequence complexity of each available viral genome using data compression, demonstrating that adequate data compressors can efficiently quantify the complexity of viral genome sequences, including sub-sequences better represented by algorithmic sources (e.g., inverted repeats). Using a state-of-the-art genomic compressor on an extensive viral genomes database, we show that dsDNA viruses are on average the most redundant viruses while ssDNA viruses are the lowest. Contrarily, dsRNA viruses show a lower redundancy relative to ssRNA. We extend the ability of data compressors to quantify local complexity (or information content) in viral genomes using complexity profiles, unprecedently providing a direct complexity analysis to human Herpesviruses. We also conceive a features-based classification methodology that can accurately distinguish viral genomes at different taxonomic levels without using direct comparisons between sequences. This methodology works by combining data compression with simple measures such as GC-content percentage and sequence length followed by machine learning classifiers. <br>This manuscript presents methodologies and findings that are highly relevant for understanding the patterns of similarity and singularity between viral groups, opening new frontiers for studying viral genomes organization while depicting the complexity trends and classification components of these genomes at different taxonomic levels. The whole study is supported by an extensive website (https://asilab.github.io/canvas/) for comprehending the viral genome characterization using dynamic and interactive approaches.
DOI: 10.5524/102245
title: Supporting data for "Selection signatures in goats reveal a novel deletion mutant underlying cashmere yield and diameter"

description: Cashmere traits were deployed for fiber yield and quality during the domestication of goats. However, the genetic alterations underlying cashmere trait selection are still unclear. We sequenced 120 Chinese native goats including two cashmere goat breeds and six ordinary goat breeds. The genome-wide selective sweep of cashmere goat and ordinary goat revealed a novel set of candidate genes as well as pathways, such as Nuclear factor kappa-B and Wnt Signaling pathways. Of them, the <i>LHX2</i> gene regulating hair follicle development, was evident from the strongest selection signal when comparing the Uhumqin cashmere goat and ordinary goat. Interestingly, we identified a 582bp deletion at 367 kb upstream of <i>LHX2</i> with higher frequency in cashmere goats and their ancient relatives. This mutation probably rises along the breeding procedures, and is putatively responsible for cashmere production and diameter, as revealed by association studies. Luciferase assay shows that the deletion, which acts as an insulator, restrains the expression of <i>LHX2</i> by interfering its upstream enhancers. Our study discovers a novel insulator of the <i>LHX2</i> involved in regulating cashmere production and diameter. Our findings also provide new insights into the genetic formation of cashmere, and facilitate subsequent molecular breeding for cashmere goat improvement.
DOI: 10.5524/102250
title: Supporting data for "BrumiR: A toolkit for de novo discovery of microRNAs from sRNA-seq data."

description: MicroRNAs (miRNAs) are small non-coding RNAs that are key players in the regulation of gene expression. In the last decade, with the increasing accessibility of high-throughput sequencing technologies, different methods have been developed to identify miRNAs, most of which rely on pre-existing reference genomes. However, when a reference genome is absent or is not of high quality, such identification becomes more difficult. In this context, we developed BrumiR, an algorithm that is able to discover miRNAs directly and exclusively from sRNA-seq data. We benchmarked BrumiR with datasets encompassing animal and plant species using real and simulated sRNA-seq experiments. The results demonstrate that BrumiR reaches the highest recall for miRNA discovery, while at the same time being much faster and more efficient than the state-of-the-art tools evaluated. The latter allows BrumiR to analyze a large number of sRNA-seq experiments, from plants or animal species. Moreover, BrumiR detects additional information regarding other expressed sequences (sRNAs, isomiRs, etc.), thus maximizing the biological insight gained from sRNA-seq experiments. Additionally, when a reference genome is available, BrumiR provides a new mapping tool (BrumiR2ref) that performs an <i>a posteriori</i> exhaustive search to identify the precursor sequences.<br>Finally, we also provide a machine learning classifier based on a Random Forest model that evaluates the sequence-derived features to further refine the prediction obtained from BrumiR-core. The code of BrumiR and all the algorithms that compose the BrumiR-toolkit are freely available in GitHub.
DOI: 10.5524/102253
title: Supporting data for "Chromosome-level genome assembly for the Aldabra giant tortoise enables insights into the genetic health of a threatened population"

description: The Aldabra giant tortoise (<i>Aldabrachelys gigantea</i>) is one of only two giant tortoise species left in the world. The species is endemic to Aldabra Atoll in Seychelles and is listed as Vulnerable on the IUCN Red List (v2.3) due to its limited distribution and threats posed by climate change. Genomic resources for <i>A. gigantea</i> are lacking, hampering conservation efforts for both wild and ex-situ populations. A high-quality genome would also open avenues to investigate the genetic basis of the species exceptionally long lifespan.<br>We produced the first chromosome-level de novo genome assembly of <i>A. gigantea</i> using PacBio High-Fidelity sequencing and high-throughput chromosome conformation capture (Hi-C). We produced a 2.37 Gbp assembly with a scaffold N50 of 148.6 Mbp and a resolution into 26 chromosomes. RNAseq-assisted gene model prediction identified 23,953 protein-coding genes and 1.1 Gbp of repetitive sequences. Synteny analyses among turtle genomes revealed high levels of chromosomal collinearity even among distantly related taxa. To assess the utility of the high-quality assembly for species conservation, we performed a low-coverage re-sequencing of 30 individuals from wild populations and two zoo individuals. Our genome-wide population structure analyses detected genetic population structure in the wild and identified the most likely origin of the zoo-housed individuals. We further identified putatively deleterious mutations to be monitored.<br>We establish a high-quality chromosome-level reference genome for <i>A. gigantea</i>, and one of the most complete turtle genomes available. We show that low-coverage whole-genome resequencing, for which alignment to the reference genome is a necessity, is a powerful tool to assess the population structure of the wild population and reveal the geographic origins of ex-situ individuals relevant for genetic diversity management and rewilding efforts.
DOI: 10.5524/102254
title: Supporting data for "A dataset of ant colonies motion trajectories in indoor and outdoor scenes to study clustering behavior"

description: Motion and interaction of social insects (such as ants) have been studied by many researchers to understand the clustering behaviour. Most studies in the field of ant behavior have only focused on indoor environments (laboratory setup), while outdoor environments (natural environments) are still underexplored. In this paper, we collect 10 videos and 3 species of ant colonies from different scenes, including 5 indoor and 5 outdoor scenes. We also develop an image sequence marking software named VisualMarkData, which enables us to provide annotations of ants in the video: (1) offers a comprehensive annotation of states at individual-target as well as colony-target levels; (2) provides a simple matrix format to represent multiple targets and multiple groups of annotations (along with their IDs and behavior labels); (3) during the annotation process, we propose a simple and effective visualization that takes the annotation information of the previous frame as a reference and then simply clicks on the center point of each target to complete the annotation; and (4) we develop a user-friendly windows-based GUI to minimize labor and maximize annotation quality. In all 5,354 frames, the location information and the identification number of each ant are recorded for a total of 712 ants and 114,112 annotations. Moreover, we provide visual analysis tools to assess and validate the technical quality and reproducibility of our data. It is hoped that this dataset will contribute to a deeper exploration of the behavior of the ant colony.