cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7270/q27s7qv8
title: BindingDB Entry 1029: Autotaxin inhibitors

description: Small molecule binding data for protein Ectonucleotide pyrophosphatase/phosphodiesterase family member 2, Uniprot Q13822
DOI: 10.7270/q2h99788
title: BindingDB Entry 1027: Isoxazole derivatives as FXR agonists and methods of use therof

description: Small molecule binding data for protein Bile acid receptor, Uniprot Q96RI1
DOI: 10.7270/q2m32xtx
title: BindingDB Entry 1034: Fused triazole derivatives as phosphodiesterase 10A inhibitors

description: Small molecule binding data for protein cAMP and cAMP-inhibited cGMP 3',5'-cyclic phosphodiesterase 10A, Uniprot Q9Y233
DOI: 10.7270/q2n30010
title: BindingDB Entry 1026: Benzimidazol-2-amines as MIDH1 inhibitors

description: Small molecule binding data for protein Cytosolic NADP-isocitrate dehydrogenase (IDH1)(R132H)
DOI: 10.7270/q2qv3pks
title: BindingDB Entry 1033: Pyrazolopyridine derivatives and their use in therapy

description: Small molecule binding data for protein PEX14-PEX5, Uniprot O75381 and Q8IYB4
DOI: 10.7270/q2vm4fbz
title: BindingDB Entry 1032: Substituted benzamides as RIPK2 inhibitors

description: Small molecule binding data for protein Serine/threonine-protein kinase RIPK2, Uniprot O43353
DOI: 10.21227/40k9-hn32
title: Deepblueberry: Quantification of Blueberries in the Wild Using Instance Segmentation

description: Deepblueberry: Quantification of Blueberries in the Wild Using Instance Segmentation Dataset.An accurate and reliable image-based quantification system for blueberries may be useful for the automation of harvest management. It may also serve as the basis for controlling robotic harvesting systems. Quantification of blueberries from images is a challenging task due to occlusions, differences in size, illumination conditions and the irregular amount of blueberries that can be present in an image. This paper proposes the quantification per image and per batch of blueberries in the wild, using high definition images captured using a mobile device. In order to quantify the number of berries per image, a network based on Mask R-CNN for object detection and instance segmentation was proposed. Several backbones such as ResNet101, ResNet50 and MobileNetV1 were tested. The performance of the algorithm was evaluated using the Intersection over Union Error (IoU) and the competitive mean Average Precision (mAP) per image and per batch. The best detection result was obtained with the ResNet50 backbone achieving a mIoU score of 0.595 and mAP scores of 0.759 and 0.724 respectively (for IoU thresholds 0.5 and 0.7). For instance segmentation, the best results obtained were 0.726 for the mIoU metric and 0.909 and 0.774 for the mAP metric using thresholds of 0.5 and 0.7 respectively.
DOI: 10.21227/rp4b-9c96
title: Deepblueberry: Quantification of Blueberries in the Wild Using Instance Segmentation

description: Deepblueberry: Quantification of Blueberries in the Wild Using Instance Segmentation Dataset.An accurate and reliable image-based quantification system for blueberries may be useful for the automation of harvest management. It may also serve as the basis for controlling robotic harvesting systems. Quantification of blueberries from images is a challenging task due to occlusions, differences in size, illumination conditions and the irregular amount of blueberries that can be present in an image. This paper proposes the quantification per image and per batch of blueberries in the wild, using high definition images captured using a mobile device. In order to quantify the number of berries per image, a network based on Mask R-CNN for object detection and instance segmentation was proposed. Several backbones such as ResNet101, ResNet50 and MobileNetV1 were tested. The performance of the algorithm was evaluated using the Intersection over Union Error (IoU) and the competitive mean Average Precision (mAP) per image and per batch. The best detection result was obtained with the ResNet50 backbone achieving a mIoU score of 0.595 and mAP scores of 0.759 and 0.724 respectively (for IoU thresholds 0.5 and 0.7). For instance segmentation, the best results obtained were 0.726 for the mIoU metric and 0.909 and 0.774 for the mAP metric using thresholds of 0.5 and 0.7 respectively.
DOI: 10.7270/q2348ng3
title: BindingDB Entry 1038: Factor XIa inhibitors

description: Small molecule binding data for protein Coagulation factor XI and Plasma kallikrein, Uniprot P03951 and P03952
DOI: 10.7270/q26w9d4m
title: BindingDB Entry 1037: Methods of treating fibrosis, cancer and vascular injuries

description: Small molecule binding data for protein TGF-beta receptor type I
DOI: 10.7270/q2bk1ff5
title: BindingDB Entry 1036: Imidazopyridine macrocycles as inhibitors of human immunodeficiency virus replication

description: Small molecule binding data for protein Envelope glycoprotein gp160, Uniprot Q72502
DOI: 10.7270/q2fb551h
title: BindingDB Entry 1048: Methods for treating cancer

description: Small molecule binding data for protein Histone-lysine N-methyltransferase, H3 lysine-79 specific, Uniprot Q8TEK3
DOI: 10.7270/q2gb2630
title: BindingDB Entry 1035: Triazolopyridines and triazolopyrazines as LSD1 inhibitors

description: Small molecule binding data for protein Lysine-specific histone demethylase 1A, Uniprot O60341
DOI: 10.7270/q2k35wq0
title: BindingDB Entry 1045: Hydroxy-substituted amino and ammonium derivatives and their medical use

description: Small molecule binding data for protein Beta-hexosaminidase subunit beta (Hex B), Uniprot P07686
DOI: 10.7270/q2pv6nfd
title: BindingDB Entry 1042: Piperazine derivatives as liver X receptor modulators

description: Small molecule binding data for protein Oxysterols receptor LXR-alpha and Oxysterols receptor LXR-beta, Uniprot P55055 and Q13133
DOI: 10.7270/q2tm7d6k
title: BindingDB Entry 1041: Immunomodulators

description: Small molecule binding data for protein Human PD-L1-TVMV-His
DOI: 10.7270/q2zc84zb
title: BindingDB Entry 1040: Pyrrolobenzodiazepines and conjugates thereof

description: Small molecule binding data for protein Receptor tyrosine-protein kinase erbB-2, Uniprot P04626
DOI: 10.25386/genetics.10136588
title: Supplemental Material for Bosch et al., 2019

description: Supplemental data (figures and tables) for the manuscript "Gene knock-ins in Drosophila using homology-independent insertion of universal donor plasmids" accepted at GENETICS
DOI: 10.5281/zenodo.3528068
title: DeepPredSpeech: computational models of predictive speech coding based on deep learning

description: This dataset contains all data, source code, pre-trained computational predictive models and experimental results related to: Hueber T., Tatulli E., Girin L., Schwatz, J-L "How predictive can be predictions in the neurocognitive processing of auditory and audiovisual speech? A deep learning study." (biorXiv preprint https://doi.org/10.1101/471581). Raw data are extracted from the publicly available database NTCD-TIMIT (10.5281/zenodo.260228). Audio recordings are available in the audio_clean/ directory Post-processed lip image sequences are available in the lips_roi/ directory (67x67 pixels, 8bits, obtained by lossless inverse DCT-2D transform from the DCT feature available in the original repository of NTCD-TIMIT) Phonetic segmentation (extracted from NTCD-TIMIT original zenodo repository) is available in the HTK MLF file volunteer_labelfiles.mlf Audio features (MFCC-spectrogram and log-spectrogram) are available in the mfcc_16k/ and fft_16k/ directories. Models (audio-only, video-only and audiovisual, based on deep feed-forward neural networks and/or convolutional neural network, in .h5 format, trained with Keras 2.0 toolkit) and data normalization parameters (in .dat scikit-learn format) are available in models_mfcc/ and models_logspectro/ directories Predicted and target (ground truth) MFCC-spectro (resp. log-spectro) for the test databases (1909 sentences), and for the different values of \(\tau_p\) or \(\tau_f\) are available in pred_testdb_mfccspectro/ (resp. pred_testdb_logspectro/) directory Source code for extracting audio features, training and evaluating the models is available on GitHub https://github.com/thueber/DeepPredSpeech/ All directories have been zipped before upload. Feel free to contact me for more details. Thomas Hueber, Ph. D., CNRS research fellow, GIPSA-lab, Grenoble, France, thomas.hueber@gipsa-lab.fr
DOI: 10.7270/q2251m8c
title: BindingDB Entry 1052: Substituted pyrazolo[1,5-A]pyridine compounds as RET kinase inhibitors

description: Small molecule binding data for protein Proto-oncogene tyrosine-protein kinase receptor Ret , RET kinase mutant (G810R), and RET kinase mutant (V804M), Uniprot P07949
DOI: 10.7270/q25x2c17
title: BindingDB Entry 1051: Nrf2 regulators

description: Small molecule binding data for protein Keap1 (321-609) and Kelch-like ECH-associated protein 1, Uniprot Q16236
DOI: 10.7270/q28p62m5
title: BindingDB Entry 1067: Chemical compounds

description: Small molecule binding data for protein Estrogen receptor, Uniprot P03372
DOI: 10.7270/q29p33q3
title: BindingDB Entry 1050: Isoxazole analogs as FXR agonists and methods of use thereof

description: Small molecule binding data for protein Bile acid receptor, Uniprot Q96RI1
DOI: 10.7270/q2nv9m91
title: BindingDB Entry 1059: Quinoxaline compounds and uses thereof

description: Small molecule binding data for protein Nicotinamide phosphoribosyltransferase, Uniprot P43490
DOI: 10.7270/q2sn0c19
title: BindingDB Entry 1058: Pyrazolo[1,5-A]PYRAZIN-4-YL derivatives

description: Small molecule binding data for protein Non-receptor tyrosine-protein kinase TYK2, Tyrosine-protein kinase JAK1, Tyrosine-protein kinase JAK2, and Tyrosine-protein kinase JAK3, Uniprot O60674, P23458, P29597, and P52333
DOI: 10.7270/q2xd13rm
title: BindingDB Entry 1055: Pyrazolo[1,5-A]PYRAZIN-4-YL derivatives

description: Small molecule binding data for protein Non-receptor tyrosine-protein kinase TYK2, Tyrosine-protein kinase JAK1, Tyrosine-protein kinase JAK2, and Tyrosine-protein kinase JAK3, Uniprot O60674, P23458, P29597, and P52333
DOI: 10.5281/zenodo.3528335
title: STEM dataset (Si impurities in graphene hole)

description: Scanning transmission electron microscopy movie (300 frames) represented as a numpy array on Si atoms moving along the edges of graphene nanohole.
DOI: 10.5281/zenodo.3528336
title: STEM dataset (Si impurities in graphene hole)

description: Scanning transmission electron microscopy movie (300 frames) represented as a numpy array on Si atoms moving along the edges of graphene nanohole.
DOI: 10.7270/q2154k3j
title: BindingDB Entry 1070: Compound of 3-hydroxyl pyridine, preparation method thereof and pharmaceutical use thereof

description: Small molecule binding data for protein Egl nine homolog 1, Uniprot Q9GZT9
DOI: 10.7270/q23x88qm
title: BindingDB Entry 1079: Mono-fluoro beta-secretase inhibitors

description: Small molecule binding data for protein Beta-secretase 1 (aa 1-460)
DOI: 10.7270/q24x59v0
title: BindingDB Entry 1069: OCT3 activity inhibitor containing imidazopyridine derivative as active component, and OCT3 detection agent

description: Small molecule binding data for protein POU domain, class 5, transcription factor 1, Uniprot Q01860
DOI: 10.7270/q2df6t8m
title: BindingDB Entry 1066: Isoxazole derivatives as FXR agonists and methods of use thereof

description: Small molecule binding data for protein Bile acid receptor, Uniprot Q96RI1
DOI: 10.7270/q2h70hwj
title: BindingDB Entry 1075: Compounds for the treatment of hepatitis C

description: Small molecule binding data for protein RNA polymerase (NS5B), Uniprot Q9WMX2
DOI: 10.7270/q2j38vnh
title: BindingDB Entry 1065: Bridged bicyclic kallikrein inhibitors

description: Small molecule binding data for protein Plasma kallikrein, Uniprot P03952
DOI: 10.7270/q2mw2k6n
title: BindingDB Entry 1073: Carboxylic acid compounds

description: Small molecule binding data for protein Toll-like receptor 7 and Toll-like receptor 8 (TLR8), Uniprot Q9NR97 and Q9NYK1
DOI: 10.7270/q2rn39wh
title: BindingDB Entry 1072: 6,7-dihydropyrido[2,1-A]phthalazin-2-ones for the treatment and prophylaxis of hepatitis B virus infection

description: Small molecule binding data for protein Hepatitis C virus polyprotein, Uniprot P26664
DOI: 10.7270/q2wd42m7
title: BindingDB Entry 1071: Alkylene derivatives

description: Small molecule binding data for protein Acetyl-CoA carboxylase 2, Uniprot O00763
DOI: 10.5281/zenodo.3480120
title: Final dataset used in our paper "Phenological shifts alter the seasonal structure of pollinator assemblages in Europe"

description: To build this dataset we merged records from 15 sources of data, listed in Extended Table 1. The way we mergre this database is described in the method part of the paper. Columns descriptor: Latitude and Longitude : WGS 84 coordinates Jday: Julian day of the record Species_mode: Species names and phenology mode (1,2,... or NA if the phenology is unimodal) Order: taxonomic order of the species Altitude: altitude got from spatial coordinates Source: Source of the data
description: Because of the protection of sensitive information about the exact location of recent populations of for instance rare butterflies to be available to everyone, we provide only 5x5km² location for data from the waarnemingen.be/observations.be databases.
DOI: 10.5281/zenodo.3528337
title: COST-ELTeC/ELTeC-fra: Release with 82 novels in level 1 encoding.

description: French novel collection for the ELTeC (European Literary Text Collection).
DOI: 10.7270/q2057j0m
title: BindingDB Entry 1081: Pyridine CDK9 kinase inhibitors

description: Small molecule binding data for protein Cyclin-dependent kinase 9, Uniprot P50750
DOI: 10.7270/q22z17ks
title: BindingDB Entry 1091: Heteroarylcarboxylic acid ester derivative

description: Small molecule binding data for protein Enteropeptidase and Trypsin-1, Uniprot P07477 and P98073
DOI: 10.7270/q27p91gs
title: BindingDB Entry 1077: ASK1 inhibitor compounds and uses thereof

description: Small molecule binding data for protein Mitogen-activated protein kinase kinase kinase 5, Myosin light chain kinase, smooth muscle, and Tumor necrosis factor, Uniprot P01375, Q15746, and Q99683
DOI: 10.7270/q2bg2r29
title: BindingDB Entry 1089: Benzamide-containing compounds and their use in the treatment of pain

description: Small molecule binding data for protein P2X purinoceptor 7, Uniprot Q99572
DOI: 10.7270/q2cf9s64
title: BindingDB Entry 1076: Pyrrolidine orexin receptor antagonists

description: Small molecule binding data for protein Orexin receptor type 1 and Orexin receptor type 2, Uniprot O43613 and O43614
DOI: 10.7270/q2g73gt2
title: BindingDB Entry 1087: Diazepinone derivatives

description: Small molecule binding data for protein Metabotropic glutamate receptor 1 and Metabotropic glutamate receptor 5, Uniprot P41594 and Q13255
DOI: 10.7270/q2m047hb
title: BindingDB Entry 1086: Sulfur-containing heterocyclic derivative having beta secretase inhibitory activity

description: Small molecule binding data for protein Beta-secretase 1, Uniprot P56817
DOI: 10.7270/q2qn68vg
title: BindingDB Entry 1085: Heterocycle-substituted pyridyl benzothiophenes as kinase inhibitors

description: Small molecule binding data for protein Interferon-induced, double-stranded RNA-activated protein kinase, Platelet-derived growth factor receptor beta, and Vascular endothelial growth factor receptor 2 and tyrosine-protein kinase TIE-2 (KDR and TIE2), Uniprot P09619, P19525, and P35968
DOI: 10.7270/q2vd71h9
title: BindingDB Entry 1083: Inhibitors

description: Small molecule binding data for protein Glutaminyl Cyclase, Uniprot Q16769
DOI: 10.7270/q21z46gv
title: BindingDB Entry 1100: Inhibitors of glutaminyl cyclase

description: Small molecule binding data for protein Glutaminyl Cyclase, Uniprot Q16769
DOI: 10.7270/q25q4z49
title: BindingDB Entry 1099: Inhibitors of Bruton's tyrosine kinase

description: Small molecule binding data for protein Epidermal growth factor receptor, Tyrosine-protein kinase BTK, Tyrosine-protein kinase BTK (C481S), Tyrosine-protein kinase JAK3, and Tyrosine-protein kinase Lck, Uniprot P00533, P06239, P52333, and Q06187
DOI: 10.7270/q26q209h
title: BindingDB Entry 1090: Therapeutic uses of selected pyrimidine compounds with anti-Mer tyrosine kinase activity

description: Small molecule binding data for protein Growth arrest-specific protein 6, Tyrosine-protein kinase Mer, Tyrosine-protein kinase receptor FLT3, and Tyrosine-protein kinase receptor TYRO3, Uniprot P36888, Q06418, and Q12866
DOI: 10.7270/q29g5pvm
title: BindingDB Entry 1098: Bicyclo[3.2.1]octyl amide derivatives and uses of same

description: Small molecule binding data for protein hmglur5 flipr, Uniprot P39086
DOI: 10.15156/bio/sh3689652.08fu
title: SH3689652.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh3689653.08fu
title: SH3689653.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh3689654.08fu
title: SH3689654.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh3689655.08fu
title: SH3689655.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh3689656.08fu
title: SH3689656.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh3689657.08fu
title: SH3689657.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.