cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8372729
title: Nanoscale electronic transport at graphene/pentacene van der Waals interface.

description: Dataset of the graphene-pentacene nanostrutures measurements related to the publication: "Nanoscale electronic transport at graphene/pentacene van der Waals interface." Nanoscale 15, 9203-9214 (2023). The dataset includes:<br> - AFM measurements<br> - Raman spectroscopy data<br> - Current-voltage data sets and the fits by analytical models.
description: Grants. - Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (CH): Hybrid Van der Waals heterostructures for vertical, permeable-base organic transistors (200021L_182544) - Agence National de la recherche scientifique (FR): Hybrid Van der Waals heterostructures for vertical, permeable-base organic transistors (ANR-18-CE93-0005-01)
description: {"references": ["Daher Mansour, M. et al. Nanoscale electronic transport at graphene/pentacene van der Waals interface. Nanoscale 15, 9203-9214 (2023)."]}
DOI: 10.6084/m9.figshare.23538141
title: curated_datasets_ucdavisicdm19.tgz

description: Curation of UCDAVIS19 dataset related to the publicationReplication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input Representation<br>Internet Traffic Measurement (IMC) 2023<br>DOI: 10.1145/3618257.3624820For information on the original dataset, please refer to@article{DBLP:journals/corr/abs-1812-09761,<br> author = {Shahbaz Rezaei and Xin Liu},<br> title = {How to Achieve High Classification Accuracy with Just a Few Labels:<br> {A} Semi-supervised Approach Using Sampled Packets},<br> journal = {CoRR},<br> volume = {abs/1812.09761},<br> year = {2018},<br> url = {http://arxiv.org/abs/1812.09761},<br> eprinttype = {arXiv},<br> eprint = {1812.09761},<br> timestamp = {Thu, 07 Nov 2019 09:05:08 +0100},<br> biburl = {https://dblp.org/rec/journals/corr/abs-1812-09761.bib},<br> bibsource = {dblp computer science bibliography, https://dblp.org}<br>}https://github.com/shrezaei/Semi-supervised-Learning-QUIC-
DOI: 10.6084/m9.figshare.23538141.v2
title: curated_datasets_ucdavisicdm19.tgz

description: Curation of UCDAVIS19 dataset related to the publicationReplication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input Representation<br>Internet Traffic Measurement (IMC) 2023<br>DOI: 10.1145/3618257.3624820For information on the original dataset, please refer to@article{DBLP:journals/corr/abs-1812-09761,<br> author = {Shahbaz Rezaei and Xin Liu},<br> title = {How to Achieve High Classification Accuracy with Just a Few Labels:<br> {A} Semi-supervised Approach Using Sampled Packets},<br> journal = {CoRR},<br> volume = {abs/1812.09761},<br> year = {2018},<br> url = {http://arxiv.org/abs/1812.09761},<br> eprinttype = {arXiv},<br> eprint = {1812.09761},<br> timestamp = {Thu, 07 Nov 2019 09:05:08 +0100},<br> biburl = {https://dblp.org/rec/journals/corr/abs-1812-09761.bib},<br> bibsource = {dblp computer science bibliography, https://dblp.org}<br>}https://github.com/shrezaei/Semi-supervised-Learning-QUIC-
DOI: 10.6084/m9.figshare.23538141.v3
title: curated_datasets_ucdavisicdm19.tgz

description: Curation of UCDAVIS19 dataset related to the publicationReplication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input Representation<br>Internet Traffic Measurement (IMC) 2023<br>DOI: 10.1145/3618257.3624820For information on the original dataset, please refer to@article{DBLP:journals/corr/abs-1812-09761,<br> author = {Shahbaz Rezaei and Xin Liu},<br> title = {How to Achieve High Classification Accuracy with Just a Few Labels:<br> {A} Semi-supervised Approach Using Sampled Packets},<br> journal = {CoRR},<br> volume = {abs/1812.09761},<br> year = {2018},<br> url = {http://arxiv.org/abs/1812.09761},<br> eprinttype = {arXiv},<br> eprint = {1812.09761},<br> timestamp = {Thu, 07 Nov 2019 09:05:08 +0100},<br> biburl = {https://dblp.org/rec/journals/corr/abs-1812-09761.bib},<br> bibsource = {dblp computer science bibliography, https://dblp.org}<br>}https://github.com/shrezaei/Semi-supervised-Learning-QUIC-
DOI: 10.6084/m9.figshare.23648703
title: curated_datasets_utmobilenet21.tgz

description: Curation of UTMobileNetTraffic2021 dataset created for the publicationReplication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input Representation<br>Internet Traffic Measurement (IMC) 2023<br>DOI: 10.1145/3618257.3624820For information on the original dataset, please refer to@ARTICLE{9490678, author={Heng, Yuqiang and Chandrasekhar, Vikram and Andrews, Jeffrey G.}, journal={IEEE Networking Letters}, title={UTMobileNetTraffic2021: A Labeled Public Network Traffic Dataset}, year={2021}, volume={3}, number={3}, pages={156-160}, doi={10.1109/LNET.2021.3098455}}<br>https://ieeexplore.ieee.org/abstract/document/9490678<br>https://github.com/YuqiangHeng/UTMobileNetTraffic2021
DOI: 10.5281/zenodo.8372812
title: acraspis_erinacei_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372811
title: acraspis_erinacei_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.23719/1520933
title: FHM reference genome, annotation, and all associated DNA and RNA-sequencing data   

description: The dataset contains the full fathead minnow (FHM) reference genome and annotation data as well all DNA sequencing data (PacBio long reads and Illumina paired-end reads) and RNA-seq data that were used to create the fathead minnow genome reference
DOI: 10.34740/kaggle/dsv/6526199
title: 📒Meta Kaggle ported to SQLITE DB
DOI: 10.5281/zenodo.8372863
title: acropternis_orthonyx_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372862
title: acropternis_orthonyx_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.25345/c5736mc5s
title: MassIVE MSV000092947 - 2023-0923 Preliminary S. coelicolor A3(2) Feeding
title: Preliminary Feeding of S. coelicolor A3(2) in BTT broth
DOI: 10.6084/m9.figshare.24187488
title: Untitled Item

description: Data on online identity's role in mental health and social comparison processes.
DOI: 10.6084/m9.figshare.24187488.v1
title: Untitled Item

description: Data on online identity's role in mental health and social comparison processes.
DOI: 10.6084/m9.figshare.24187500
title: <b>Morpho-Phylogenetic Evidence reveals novel species and new</b> <b>records of</b> <b><i>Botryosphaeriaceae</i></b> <b>in China and Thailand</b>m

description: <i>Botryosphaeriaceae</i>: Phylogenetic tree generated from maximum likelihood (ML) analysis based on combined ITS, LSU, <i>tef1-</i><i>α</i> and <i>tub2</i> sequence 159 data for selected closely related genera within the family <i>Botryosphaeriaceae</i>.<br><i>Dothiorella</i>: Phylogenetic tree generated from the maximum likelihood (ML) analysis based on combined ITS, LSU, <i>tef1-</i><i>α</i> and <i>tub2</i> 166 sequence data of <i>Dothiorella</i>.
DOI: 10.6084/m9.figshare.24187500.v1
title: <b>Morpho-Phylogenetic Evidence reveals novel species and new</b> <b>records of</b> <b><i>Botryosphaeriaceae</i></b> <b>in China and Thailand</b>m

description: <i>Botryosphaeriaceae</i>: Phylogenetic tree generated from maximum likelihood (ML) analysis based on combined ITS, LSU, <i>tef1-</i><i>α</i> and <i>tub2</i> sequence 159 data for selected closely related genera within the family <i>Botryosphaeriaceae</i>.<br><i>Dothiorella</i>: Phylogenetic tree generated from the maximum likelihood (ML) analysis based on combined ITS, LSU, <i>tef1-</i><i>α</i> and <i>tub2</i> 166 sequence data of <i>Dothiorella</i>.
DOI: 10.5281/zenodo.8372894
title: CLIMBER-X time series output of simulated Dansgaard-Oeschger events

description: CLIMBER-X time series output of simulations showing Dansgaard-Oeschger -like events. The amoc_* files contain the time series of the maximum Atlantic overturning streamfunction for the simulations with different ice sheets and atmospheric CO2 concentrations as specified in the file name. The ocn_ts_* files contain the time series of the maximum Atlantic overturning streamfunction and the buoyancy flux integrated north of 55°N in the North Atlantic for the simulations with different ice sheets and gradually decreasing or increasing atmospheric CO2 concentration as specified in the file name. File names ending with *_noise.nc are for simulations with noise and those ending with *_nonoise.nc are for simulations without applied noise.
DOI: 10.34740/kaggle/dsv/6526431
title: Vietnam SARS-CoV-2 | COVID-19 Data
DOI: 10.5281/zenodo.8372908
title: agapornis_nigrigenis_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372907
title: agapornis_nigrigenis_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.6084/m9.figshare.24187524
title: Giere et al_MS submitted to EJN

description: Graphpad file containing data shown in manuscript
DOI: 10.6084/m9.figshare.24187524.v2
title: Giere et al_MS submitted to EJN

description: Graphpad file containing data shown in manuscript
DOI: 10.6084/m9.figshare.24187524.v1
title: Giere_Figure4_Ephy-Single.pzf

description: Graphpad file containing data shown in figure 4
DOI: 10.5281/zenodo.8372913
title: anabacerthia_variegaticeps_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372912
title: anabacerthia_variegaticeps_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372915
title: andricus_quercuspetiolicola_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372914
title: andricus_quercuspetiolicola_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372917
title: anisognathus_igniventris_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372916
title: anisognathus_igniventris_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372923
title: arremon_aurantiirostris_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372922
title: arremon_aurantiirostris_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372931
title: arremon_brunneinucha_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372930
title: arremon_brunneinucha_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372935
title: cacatua_galerita_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372934
title: cacatua_galerita_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372937
title: crypturellus_boucardi_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372936
title: crypturellus_boucardi_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372943
title: eueides_aliphera_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372942
title: eueides_aliphera_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372947
title: eueides_lybia_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8372946
title: eueides_lybia_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8242882
title: Dataset of scientific article "Variability in Arsenic Methylation Efficiency across Aerobic and Anaerobic Microorganisms"

description: Dataset for journal paper entitled "Variability in Arsenic Methylation Efficiency across Aerobic and Anaerobic Microorganisms".
description: The work was funded by the Swiss National Science Foundation (SNSF) grant 310030_176146, an SNSF professorship grant PP00P2_163661, the SNSF National Center of Competence in Research "Microbiomes", and the UK Biotechnology and Biological Sciences Research Council grants BB/J014508/1718 and BB/L013940/1.
DOI: 10.6084/m9.figshare.24187602
title: EAM FFs

description: EAM FFshttps://iopscience.iop.org/article/10.1088/1361-648X/aadaff/meta
DOI: 10.34740/kaggle/ds/3763347
title: Pokemon Stats All Gens with Competitive Values
DOI: 10.5281/zenodo.8371195
title: Simultaneous estimation of gene regulatory network structure and RNA kinetics from single cell gene expression

description: Supplemental Data 1 is single-cell response to rapamycin count data first sequenced in this work and deposited in GEO with accession GSE242556. It is a 173348 rows × 5847 columns TSV.GZ file where the first row is a header, the first 5843 columns are integer gene counts, and the final 4 columns ('Gene', 'Replicate', 'Pool', and 'Experiment') are cell-specific metadata. Supplemental Data 2 is bulk response to rapamycin count data first sequenced in this work. It is a 33 rows × 5847 columns TSV.GZ file where the first row is a header, the first 5843 columns are integer gene counts, and the final 4 columns ('Oligo', 'Time', 'Replicate', and 'Sample_barcode') are sample-specific metadata. Supplemental Data 3 is single-cell count data published as GSE125162 and re-analyzed with the pipeline used for single-cell quantification in this work. It is a 65068 rows × 5850 columns TSV.GZ file where the first row is a header, the first 5843 columns are integer gene counts, and the final 7 columns ('Condition', 'Sample', 'Genotype_Group', 'Genotype_Individual', 'Genotype', 'Replicate', 'Cell_Barcode') are cell-specific metadata. Supplemental Data 4 is the four deep learning models trained in this work. It is a TAR.GZ file containing the final biophysical transcription/decay model, the pre-trained decay model, the velocity prediction model, and the count prediction model. Each model file is an h5 file containing a pytorch model that can be loaded with supirfactor\_dynamical.read(). Supplemental Data 5 is the prior knowledge network used to constrain the models for TF interpretability. It is a 1574 rows × 204 columns [Genes x TFs] TSV.GZ file where the first row is a header with TF names, the first column is an index of gene names, and TF-gene interactions are indicated by non-zero values in the matrix. There are 2799 TF-gene interactions. <br> Supplemental Table 6 is the oligonucleotide sequences used in this work. It is a TSV file with a header row. Supplemental Table 7 is the yeast strains used in this work. It is a TSV file with a header row. Supplemental Table 8 is gene metadata used in this work (e.g. Ribosomal Protein gene labels, etc). It is a TSV file with a header row. Supplemental Table 9 is FY4/5 growth curve data generated in this work. It is a 20 rows × 7 columns TSV file where the first row is a header with replicate IDs, the first column is an index of times in minutes, and values are cell densities in YPD culture, in units of 10$^6$ cells / mL. Supplemental Data 10 is a TAR.GZ file containing the yeast SacCer3 genome, modified to add UTR sequences, that was used to generate transcripts for kallisto pseudoalignment in this work.
DOI: 10.5281/zenodo.8371194
title: Simultaneous estimation of gene regulatory network structure and RNA kinetics from single cell gene expression

description: Supplemental Data 1 is single-cell response to rapamycin count data first sequenced in this work and deposited in GEO with accession GSE242556. It is a 173348 rows × 5847 columns TSV.GZ file where the first row is a header, the first 5843 columns are integer gene counts, and the final 4 columns ('Gene', 'Replicate', 'Pool', and 'Experiment') are cell-specific metadata. Supplemental Data 2 is bulk response to rapamycin count data first sequenced in this work. It is a 33 rows × 5847 columns TSV.GZ file where the first row is a header, the first 5843 columns are integer gene counts, and the final 4 columns ('Oligo', 'Time', 'Replicate', and 'Sample_barcode') are sample-specific metadata. Supplemental Data 3 is single-cell count data published as GSE125162 and re-analyzed with the pipeline used for single-cell quantification in this work. It is a 65068 rows × 5850 columns TSV.GZ file where the first row is a header, the first 5843 columns are integer gene counts, and the final 7 columns ('Condition', 'Sample', 'Genotype_Group', 'Genotype_Individual', 'Genotype', 'Replicate', 'Cell_Barcode') are cell-specific metadata. Supplemental Data 4 is the four deep learning models trained in this work. It is a TAR.GZ file containing the final biophysical transcription/decay model, the pre-trained decay model, the velocity prediction model, and the count prediction model. Each model file is an h5 file containing a pytorch model that can be loaded with supirfactor\_dynamical.read(). Supplemental Data 5 is the prior knowledge network used to constrain the models for TF interpretability. It is a 1574 rows × 204 columns [Genes x TFs] TSV.GZ file where the first row is a header with TF names, the first column is an index of gene names, and TF-gene interactions are indicated by non-zero values in the matrix. There are 2799 TF-gene interactions. <br> Supplemental Table 6 is the oligonucleotide sequences used in this work. It is a TSV file with a header row. Supplemental Table 7 is the yeast strains used in this work. It is a TSV file with a header row. Supplemental Table 8 is gene metadata used in this work (e.g. Ribosomal Protein gene labels, etc). It is a TSV file with a header row. Supplemental Table 9 is FY4/5 growth curve data generated in this work. It is a 20 rows × 7 columns TSV file where the first row is a header with replicate IDs, the first column is an index of times in minutes, and values are cell densities in YPD culture, in units of 10$^6$ cells / mL. Supplemental Data 10 is a TAR.GZ file containing the yeast SacCer3 genome, modified to add UTR sequences, that was used to generate transcripts for kallisto pseudoalignment in this work.
DOI: 10.34740/kaggle/dsv/6526956
title: Balochi Language to English Translation Dataset
DOI: 10.5281/zenodo.8361822
title: Column size for direct displacement based design of base-isolated RC frame buildings

description: In this paper, a method of computer-added program-based algorithm is introduced to evaluate the possible floor-wise column size for direct displacement-based design of base-isolated reinforced concrete frame buildings. The design storey drifts are kept low as base isolated buildings are mostly intended to achieve low storey drift fully-operational performance level under spectrum-compatible ground motions. Lead rubber bearing is used as base isolator and designed according to the UBC-97 maximum vertical load method. The frame deformation components considered in the algorithm are column tip displacement due to flexure, average column displacement due to shear, and joint rotation due to flexure and shear. It was observed that the proposed method effectively determines the storey-wise column size for various building plans, heights upto 9-storey and base displacement upto 350mm for target storey drift upto 0.25%.
DOI: 10.5281/zenodo.8373042
title: Column size for direct displacement based design of base-isolated RC frame buildings

description: In this paper, a method of computer-added program-based algorithm is introduced to evaluate the possible floor-wise column size for direct displacement-based design of base-isolated reinforced concrete frame buildings. The design storey drifts are kept low as base isolated buildings are mostly intended to achieve low storey drift fully-operational performance level under spectrum-compatible ground motions. Lead rubber bearing is used as base isolator and designed according to the UBC-97 maximum vertical load method. The frame deformation components considered in the algorithm are column tip displacement due to flexure, average column displacement due to shear, and joint rotation due to flexure and shear. It was observed that the proposed method effectively determines the storey-wise column size for various building plans, heights upto 9-storey and base displacement upto 350mm for target storey drift upto 0.25%.
DOI: 10.5281/zenodo.8371084
title: Dynamics and maintenance of categorical responses in primary auditory cortex during task engagement

description: Source data used in the paper: "Dynamics and maintenance of categorical responses in primary auditory cortex during task engagement" (BiorXiv, 2022), Chillale RK, Shamma S, Ostojic S, Boubenec Y. (doi: https://doi.org/10.1101/2022.12.19.521141) This data repository contains following folders: <br> - Pelardon (Ferret-P) and Timanoix(Ferret-T) as described in the figures of the paper<br> - Each folder contains sub-folders 1. Spike_soring and 2. TrialStructures and Channels_all.mat and SessionsInfo_AllSess.mat<br> - This data can used to generate figures in the paper using publicly available code (https://github.com/rupeshjnu/A1-Category) <br> - Spike_sorting folder contains recording sessions corresponding to SessionInfo_AllSess.mat file with the session number mentioned in the code<br> - Each Spike_sorting folder contains files<br> - TrialStructure folders corresponds to behavioral files corresponding to the recording sessions <br>
description: {"references": ["doi: https://doi.org/10.1101/2022.12.19.521141"]}
DOI: 10.5281/zenodo.8371083
title: Dynamics and maintenance of categorical responses in primary auditory cortex during task engagement

description: Source data used in the paper: "Dynamics and maintenance of categorical responses in primary auditory cortex during task engagement" (BiorXiv, 2022), Chillale RK, Shamma S, Ostojic S, Boubenec Y. (doi: https://doi.org/10.1101/2022.12.19.521141) This data repository contains following folders: <br> - Pelardon (Ferret-P) and Timanoix(Ferret-T) as described in the figures of the paper<br> - Each folder contains sub-folders 1. Spike_soring and 2. TrialStructures and Channels_all.mat and SessionsInfo_AllSess.mat<br> - This data can used to generate figures in the paper using publicly available code (https://github.com/rupeshjnu/A1-Category) <br> - Spike_sorting folder contains recording sessions corresponding to SessionInfo_AllSess.mat file with the session number mentioned in the code<br> - Each Spike_sorting folder contains files<br> - TrialStructure folders corresponds to behavioral files corresponding to the recording sessions <br>
description: {"references": ["doi: https://doi.org/10.1101/2022.12.19.521141"]}
DOI: 10.34740/kaggle/ds/3770174
title: Longs and Meeker Mountain Peaks in Colorado
DOI: 10.5281/zenodo.7726176
title: Dataset Graph 1: Heiner Müller's Publications 1960–1998.

description: Dataset for Graph 1. Data collected based on the Heiner Müller Werkausgabe. Graph 1 depicts Müller’s publication record regarding his public-oriented writings from the early stages of his career in the 1960s until two years after his death in 1998.
description: {"references": ["M\u00fcller, Heiner. Werke, edited by Frank H\u00f6rnigk. Frankfurt am Main: Suhrkamp, 1998."]}
DOI: 10.5281/zenodo.7726175
title: Dataset Graph 1: Heiner Müller's Publications 1960–1998.

description: Dataset for Graph 1. Data collected based on the Heiner Müller Werkausgabe. Graph 1 depicts Müller’s publication record regarding his public-oriented writings from the early stages of his career in the 1960s until two years after his death in 1998.
description: {"references": ["M\u00fcller, Heiner. Werke, edited by Frank H\u00f6rnigk. Frankfurt am Main: Suhrkamp, 1998."]}
DOI: 10.5281/zenodo.7726189
title: Dataset Graph 2: Publication Type and Venue of Heiner Müller's Writings

description: Dataset for Graph 2. Data collected based on the Heiner Müller Werkausgabe. Graph 2 shows the different publication types and publication venues that Heiner Müller used to publish his writings (essays, articles, speeches, etc.) from 1968 until 1998.
description: {"references": ["M\u00fcller, Heiner. Werke, edited by Frank H\u00f6rnigk. Frankfurt am Main: Suhrkamp, 1998."]}
DOI: 10.5281/zenodo.7726188
title: Dataset Graph 2: Publication Type and Venue of Heiner Müller's Writings

description: Dataset for Graph 2. Data collected based on the Heiner Müller Werkausgabe. Graph 2 shows the different publication types and publication venues that Heiner Müller used to publish his writings (essays, articles, speeches, etc.) from 1968 until 1998.
description: {"references": ["M\u00fcller, Heiner. Werke, edited by Frank H\u00f6rnigk. Frankfurt am Main: Suhrkamp, 1998."]}