cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1135718.10fu
title: SH1135718.10FU

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/sh1135720.10fu
title: SH1135720.10FU

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/sh1135724.10fu
title: SH1135724.10FU

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: 10.15468/dl.4sdz89
title: Occurrence Download

description: A dataset containing 113 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Canada",
 "Country is Canada"
 ]
 },
 {
 "and" : [
 "CollectionKey is one of (65f33b76-9146-4058-b769-75b7d9ffe2b4)",
 "RecordedBy is one of (McNeil, Raymond, Lebeuf, Renée, McNeil, Raymond; Lebeuf, Renée, Lebeuf, Renée; McNeil, Raymond, Archambault, Raymond; Lebeuf, Renée)",
 "Year is 2011",
 "Locality is one of (Réserve écologique du Boisé-des-Muir, Hinchinbrooke., Châteauguay)"
 ]
 }
 ]
}

 The dataset includes 113 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002662-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1135725.10fu
title: SH1135725.10FU

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/sh1135726.10fu
title: SH1135726.10FU

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: 10.15468/dl.rmwjqs
title: Occurrence Download

description: A dataset containing 32890144 species occurrences available in GBIF matching the query:
{
 "or" : [
 "Country is Spain",
 "Country is Portugal",
 "Country is Andorra",
 "Country is Gibraltar"
 ]
}

 The dataset includes 32890144 records from 1718 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018657-181003121212138/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/v00ce39f
title: Tumor size measurements in mice

description: The dataset used in this paper is a collection of tumor size measurements along time in three groups of mice: a control group, a group treated with ACT therapy, and a group treated with ACT therapy and restimulation.
DOI: 10.57702/nugf8iwc
title: Grid World Navigation Task

description: The dataset used in the paper is a grid world navigation task with four actions: up, down, left, or right. Transitions are stochastic and with a 5% probability the agent moves sideways. Rewards are set to 1 for entering the goal cell (terminal state) in the top right corner, and otherwise a zero reward is given.
DOI: 10.15468/dl.63pumv
title: Occurrence Download

description: A dataset containing 35361 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chaetocerotaceae",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 35361 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037156-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/0jn8mo19
title: Grid2Op

description: The dataset is a power grid simulator built on Grid2Op, an existing simulator and RL interface.
DOI: 10.25378/janelia.24256090
title: Manual organelle segmentations (crop228) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of (jrc_ut21-1413-003)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of extracellular space, plasma membrane, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum lumen, endoplasmic reticulum membrane, lipid droplet lumen, lipid droplet membrane, lysosome lumen, lysosome membrane, endosome lumen, cytosol, lysosome, endosome, vesicle, lipid droplet, endoplasmic reticulum, cell, endoplasmic reticulum membrane collective in jrc_ut21-1413-003 using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop228<b>Primary Annotator</b>: Woohyun Park<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 4 x 4 x 4 (x, y, z)<b>Annotated data dimensions (µm)</b>: 1.6 x 1.6 x 1.6 (x, y, z)<b>Annotated data offset (nm)</b>: 68558 x 48398 x 62534 (x, y, z)<b>Classes annotated</b>: extracellular space, plasma membrane, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum lumen, endoplasmic reticulum membrane, lipid droplet lumen, lipid droplet membrane, lysosome lumen, lysosome membrane, endosome lumen, cytosol, lysosome, endosome, vesicle, lipid droplet, endoplasmic reticulum, cell, endoplasmic reticulum membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_ut21-1413-003/jrc_ut21-1413-003.zarr/recon-1/labels/groundtruth/crop228<b>Source (EM) dataset ID</b>: jrc_ut21-1413-003<b>Source (EM) voxel size (nm)</b>: 8 x 8 x 8 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 130.42 x 91.22 x 121.19 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.27075529<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_ut21-1413-003<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25378/janelia.24256090.v1
title: Manual organelle segmentations (crop228) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of (jrc_ut21-1413-003)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of extracellular space, plasma membrane, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum lumen, endoplasmic reticulum membrane, lipid droplet lumen, lipid droplet membrane, lysosome lumen, lysosome membrane, endosome lumen, cytosol, lysosome, endosome, vesicle, lipid droplet, endoplasmic reticulum, cell, endoplasmic reticulum membrane collective in jrc_ut21-1413-003 using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop228<b>Primary Annotator</b>: Woohyun Park<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 4 x 4 x 4 (x, y, z)<b>Annotated data dimensions (µm)</b>: 1.6 x 1.6 x 1.6 (x, y, z)<b>Annotated data offset (nm)</b>: 68558 x 48398 x 62534 (x, y, z)<b>Classes annotated</b>: extracellular space, plasma membrane, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum lumen, endoplasmic reticulum membrane, lipid droplet lumen, lipid droplet membrane, lysosome lumen, lysosome membrane, endosome lumen, cytosol, lysosome, endosome, vesicle, lipid droplet, endoplasmic reticulum, cell, endoplasmic reticulum membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_ut21-1413-003/jrc_ut21-1413-003.zarr/recon-1/labels/groundtruth/crop228<b>Source (EM) dataset ID</b>: jrc_ut21-1413-003<b>Source (EM) voxel size (nm)</b>: 8 x 8 x 8 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 130.42 x 91.22 x 121.19 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.27075529<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_ut21-1413-003<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.57702/af7d9v3v
title: rte_case5_example

description: The dataset is a power grid simulator with 5 substations and 11 loads.
DOI: 10.57702/t50euam8
title: rte_case14_realistic

description: The dataset is a power grid simulator with 14 substations and 5 generators.
DOI: 10.57702/eb2veylw
title: Human Activity Recognition using Smartphone

description: Human activity recognition has wide applications in medical research and human survey system. In this project, we design a robust activity recognition system based on a smartphone.
DOI: 10.57702/89etg4lf
title: Offensive Language Identiﬁcation Dataset (OLID)

description: The Offensive Language Identiﬁcation Dataset (OLID) is a large collection of English tweets annotated for offensive language use, following a three-level hierarchical schema that considers whether a message is offensive or not, what is the type of the offensive message, and who is the target of the offensive message.
DOI: 10.57702/pzluhxyu
title: Hate Speech Tweets dataset

description: The Hate Speech Tweets dataset contains over 24,000 English tweets labeled as non-offensive, hate speech, and profanity.
DOI: 10.6084/m9.figshare.c.3614792_d5.v1
title: Additional file 6: Software. of Intraspecific rearrangement of mitochondrial genome suggests the prevalence of the tandem duplication-random loss (TDLR) mechanism in Quasipaa boulengeri

description: The Perl script mtGordV0.5.pl with its readme file and example input and output files. (ZIP 5.35 kb)
DOI: 10.57702/ggiwbiee
title: Toxic Comment Classification Challenge dataset

description: The Toxic Comment Classification Challenge dataset contains comments from Wikipedia organized in six classes: toxic, severe toxic, obscene, threat, insult, and identity hate.
DOI: 10.6084/m9.figshare.c.3614792_d2.v1
title: Additional file 2: Table S2. of Intraspecific rearrangement of mitochondrial genome suggests the prevalence of the tandem duplication-random loss (TDLR) mechanism in Quasipaa boulengeri

description: The gene organization of â  WANCYâ   region for each sample. (XLS 77 kb)
DOI: 10.6084/m9.figshare.c.3614792_d3.v1
title: Additional file 1: Table S1. of Intraspecific rearrangement of mitochondrial genome suggests the prevalence of the tandem duplication-random loss (TDLR) mechanism in Quasipaa boulengeri

description: Summary of sample localities and mitogenome regions sequenced for Quasipaa boulengeri. (XLS 84 kb)
DOI: 10.57702/5ema773e
title: TENet: Triple Excitation Network for Video Salient Object Detection

description: A video salient object detection method equipped with a triple excitation mechanism.
DOI: 10.57702/hhk7ea10
title: SSAV: Salient Object Detection via Attention-based Visual Flow

description: A video salient object detection method using optical flow.
DOI: 10.6084/m9.figshare.c.3614714_d12.v1
title: Additional file 11: of Expression of OsMYB55 in maize activates stress-responsive genes and enhances heat and drought tolerance

description: DEG in MYB55 line leaf control condition associated to drought response/tolerance. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.c.3614726_d5.v1
title: Additional file 3: Table S2. of Transcriptome analysis indicated that Salmonella lipopolysaccharide-induced thymocyte death and thymic atrophy were related to TLR4-FOS/JUN pathway in chicks

description: Detailed information on IPA pathway analysis of DETs at different time points. a Over-represented pathways from up-expressed DETs at 12 hpt. b Over-represented pathways from down-expressed DETs at 12 hpt. c Over-represented pathways from up-expressed DETs at 36 hpt. d Over-represented pathways from down-expressed DETs at 36 hpt. e Over-represented pathways from up-expressed DETs at 72 hpt. f Over-represented pathways from down-expressed DETs. IPA pathways with Pâ
DOI: 10.57702/gvk1497v
title: Pyramid dilated deeper convlstm for video salient object detection

description: A video salient object detection method using pyramid dilated deeper convlstm.
DOI: 10.6084/m9.figshare.c.3614714_d10.v1
title: Additional file 2: of Expression of OsMYB55 in maize activates stress-responsive genes and enhances heat and drought tolerance

description: Expressed genes and alignment percentages in all samples. (XLSX 12 kb)
DOI: 10.25378/janelia.24263476
title: Manual organelle segmentations (crop378) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of zebrafish cardiac tisue pilot 1a; 7dpf (jrc_zf-cardiac-1)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of nucleus in jrc_zf-cardiac-1 using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop378<b>Primary Annotator</b>: Diana Ramirez<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 32 x 32 x 32 (x, y, z)<b>Annotated data dimensions (µm)</b>: 16 x 16 x 16 (x, y, z)<b>Annotated data offset (nm)</b>: 67212 x 48012 x 251212 (x, y, z)<b>Classes annotated</b>: nucleus<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_zf-cardiac-1/jrc_zf-cardiac-1.zarr/recon-1/labels/groundtruth/crop378Formula fields should be configured in the field menu dropdown<br><b>Source (EM) dataset ID</b>: jrc_zf-cardiac-1<b>Source (EM) voxel size (nm)</b>: 8 x 8 x 8 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 165.03 x 158.51 x 321.22 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.22630519<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_zf-cardiac-1<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25378/janelia.24263476.v1
title: Manual organelle segmentations (crop378) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of zebrafish cardiac tisue pilot 1a; 7dpf (jrc_zf-cardiac-1)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of nucleus in jrc_zf-cardiac-1 using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop378<b>Primary Annotator</b>: Diana Ramirez<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 32 x 32 x 32 (x, y, z)<b>Annotated data dimensions (µm)</b>: 16 x 16 x 16 (x, y, z)<b>Annotated data offset (nm)</b>: 67212 x 48012 x 251212 (x, y, z)<b>Classes annotated</b>: nucleus<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_zf-cardiac-1/jrc_zf-cardiac-1.zarr/recon-1/labels/groundtruth/crop378Formula fields should be configured in the field menu dropdown<br><b>Source (EM) dataset ID</b>: jrc_zf-cardiac-1<b>Source (EM) voxel size (nm)</b>: 8 x 8 x 8 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 165.03 x 158.51 x 321.22 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.22630519<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_zf-cardiac-1<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.6084/m9.figshare.c.3614726_d4.v1
title: Additional file 2: Table S1. of Transcriptome analysis indicated that Salmonella lipopolysaccharide-induced thymocyte death and thymic atrophy were related to TLR4-FOS/JUN pathway in chicks

description: Detailed information on DETs at different time points. a Up-expressed DETs at 12 hpt. b Down-expressed DETs at 12 hpt. c Up-expressed DETs at 36 hpt. d Down-expressed DETs at 36 hpt. e Up-expressed DETs at 72 hpt. f Down-expressed DETs at 72 hpt. Transcripts were considered as DETs only with absolute fold changes ≥ 1.5 and P
DOI: 10.57702/s99hhluh
title: Pyramid feature attention network for saliency detection

description: A saliency detection method using pyramid feature attention network.
DOI: 10.57702/gg5rbs9w
title: COVID-19 data

description: The COVID-19 pandemic has created turmoil in the lives of millions of people across the globe. Even with the advent of vaccines, their distribution remains a challenge.