cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12082575
title: Additional file 9 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 9 Table S7. Clinical information of 30 cases CRC patients in GSE110225.
DOI: 10.6084/m9.figshare.12082569
title: Additional file 2 of Integrative bioinformatics analysis reveals miR-494 and its target genes as predictive biomarkers of trastuzumab-resistant breast cancer

description: Additional file 2: Table S1. DEGs from GSE101841.
DOI: 10.6084/m9.figshare.12082572
title: Additional file 3 of Integrative bioinformatics analysis reveals miR-494 and its target genes as predictive biomarkers of trastuzumab-resistant breast cancer

description: Additional file 3: Table S2. DEGs from GSE75669.
DOI: 10.6084/m9.figshare.12082578.v1
title: Additional file 4 of Integrative bioinformatics analysis reveals miR-494 and its target genes as predictive biomarkers of trastuzumab-resistant breast cancer

description: Additional file 4: Table S3. DEGs from GSE66305.
DOI: 10.6084/m9.figshare.12082575.v1
title: Additional file 9 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 9 Table S7. Clinical information of 30 cases CRC patients in GSE110225.
DOI: 10.6084/m9.figshare.12082566
title: Additional file 8 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 8 Table S6. Clinical information of 156 cases CRC patients in Cohort 2.
DOI: 10.6084/m9.figshare.12082569.v1
title: Additional file 2 of Integrative bioinformatics analysis reveals miR-494 and its target genes as predictive biomarkers of trastuzumab-resistant breast cancer

description: Additional file 2: Table S1. DEGs from GSE101841.
DOI: 10.6084/m9.figshare.12082560
title: Additional file 7 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 7 Table S5. Clinical information of 47 cases CRC patients in Cohort 1.
DOI: 10.6084/m9.figshare.12082572.v1
title: Additional file 3 of Integrative bioinformatics analysis reveals miR-494 and its target genes as predictive biomarkers of trastuzumab-resistant breast cancer

description: Additional file 3: Table S2. DEGs from GSE75669.
DOI: 10.6084/m9.figshare.12082566.v1
title: Additional file 8 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 8 Table S6. Clinical information of 156 cases CRC patients in Cohort 2.
DOI: 10.6084/m9.figshare.12082560.v1
title: Additional file 7 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 7 Table S5. Clinical information of 47 cases CRC patients in Cohort 1.
DOI: 10.6084/m9.figshare.12082554
title: Additional file 6 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 6 Table S4. m6A-seq analysis in HCT116 WT and METTL3-knockout cells.
DOI: 10.6084/m9.figshare.12082554.v1
title: Additional file 6 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 6 Table S4. m6A-seq analysis in HCT116 WT and METTL3-knockout cells.
DOI: 10.6084/m9.figshare.12082539
title: Additional file 4 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 4 Table S2. Pathways regulated by METTL3 in HCT116 cells.
DOI: 10.6084/m9.figshare.12082545
title: Additional file 5 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 5 Table S3. Metabolites of glycolysis pathway measured by Liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) in HCT116 WT and METTL3-knockout cells.
DOI: 10.6084/m9.figshare.12082539.v1
title: Additional file 4 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 4 Table S2. Pathways regulated by METTL3 in HCT116 cells.
DOI: 10.6084/m9.figshare.12082545.v1
title: Additional file 5 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 5 Table S3. Metabolites of glycolysis pathway measured by Liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) in HCT116 WT and METTL3-knockout cells.
DOI: 10.6084/m9.figshare.12082527
title: Additional file 2 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 2 Table S1. RNA-seq analysis in HCT116 WT and METTL3-knockout cells.
DOI: 10.6084/m9.figshare.12082527.v1
title: Additional file 2 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 2 Table S1. RNA-seq analysis in HCT116 WT and METTL3-knockout cells.
DOI: 10.6084/m9.figshare.12082512
title: Additional file 10 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 10 Table S8. The sequences of siRNAs and primers used this study.
DOI: 10.6084/m9.figshare.12082512.v1
title: Additional file 10 of m6A-dependent glycolysis enhances colorectal cancer progression

description: Additional file 10 Table S8. The sequences of siRNAs and primers used this study.
DOI: 10.6084/m9.figshare.12082485
title: Additional file 1 of Dysbiosis of saliva microbiome in patients with oral lichen planus

description: Additional file 1: Figure S4. The Box-plot of higher relative abundance in genus level. The ordinate represents the classification attribute, phylum, and genera level. The abscissa represents the reading abundance. The boxed line near the left of the vertical axis represents the lower quartile, which accounts for 25% of all values in the sample arranged in an ascending order. The vertical line of the box is the median, which accounts for 50% of all values in the sample arranged in an ascending order. The black square in picture shows the higher or lower relative abundance bacteria in E or NE OLP group.
DOI: 10.6084/m9.figshare.12082479
title: Additional file 2 of Full-term low birth weight infants have differentially hypermethylated DNA related to immune system and organ growth: a comparison with full-term normal birth weight infants

description: Additional file 2: Table S1. Maternal and infant characteristics in DNA methylation analysis.
DOI: 10.6084/m9.figshare.12082485.v1
title: Additional file 1 of Dysbiosis of saliva microbiome in patients with oral lichen planus

description: Additional file 1: Figure S4. The Box-plot of higher relative abundance in genus level. The ordinate represents the classification attribute, phylum, and genera level. The abscissa represents the reading abundance. The boxed line near the left of the vertical axis represents the lower quartile, which accounts for 25% of all values in the sample arranged in an ascending order. The vertical line of the box is the median, which accounts for 50% of all values in the sample arranged in an ascending order. The black square in picture shows the higher or lower relative abundance bacteria in E or NE OLP group.
DOI: 10.6084/m9.figshare.12082479.v1
title: Additional file 2 of Full-term low birth weight infants have differentially hypermethylated DNA related to immune system and organ growth: a comparison with full-term normal birth weight infants

description: Additional file 2: Table S1. Maternal and infant characteristics in DNA methylation analysis.
DOI: 10.6084/m9.figshare.12082464
title: Additional file 3 of Label free proteomics and systematic analysis of secretome reveals effector candidates regulated by SGE1 and FTF1 in the plant pathogen Fusarium oxysporum f. sp. cubense tropical race 4

description: Additional file 3 Table S3. Predicted binding sites of SGE1 and FTF1 in the promoters of effector candidates.
DOI: 10.6084/m9.figshare.12082461
title: Additional file 2 of Label free proteomics and systematic analysis of secretome reveals effector candidates regulated by SGE1 and FTF1 in the plant pathogen Fusarium oxysporum f. sp. cubense tropical race 4

description: Additional file 2 Table S2. Classification of effector candidates based on their abundance changes.
DOI: 10.6084/m9.figshare.12082455
title: Additional file 1 of Label free proteomics and systematic analysis of secretome reveals effector candidates regulated by SGE1 and FTF1 in the plant pathogen Fusarium oxysporum f. sp. cubense tropical race 4

description: Additional file 1 Table S1. Proteins detected in the secretome through LC-MS/MS analysis.
DOI: 10.6084/m9.figshare.12082464.v1
title: Additional file 3 of Label free proteomics and systematic analysis of secretome reveals effector candidates regulated by SGE1 and FTF1 in the plant pathogen Fusarium oxysporum f. sp. cubense tropical race 4

description: Additional file 3 Table S3. Predicted binding sites of SGE1 and FTF1 in the promoters of effector candidates.
DOI: 10.6084/m9.figshare.12082461.v1
title: Additional file 2 of Label free proteomics and systematic analysis of secretome reveals effector candidates regulated by SGE1 and FTF1 in the plant pathogen Fusarium oxysporum f. sp. cubense tropical race 4

description: Additional file 2 Table S2. Classification of effector candidates based on their abundance changes.
DOI: 10.6084/m9.figshare.12082455.v1
title: Additional file 1 of Label free proteomics and systematic analysis of secretome reveals effector candidates regulated by SGE1 and FTF1 in the plant pathogen Fusarium oxysporum f. sp. cubense tropical race 4

description: Additional file 1 Table S1. Proteins detected in the secretome through LC-MS/MS analysis.
DOI: 10.6084/m9.figshare.12082440
title: Additional file 3 of Re-annotation of the Theileria parva genome refines 53% of the proteome and uncovers essential components of N-glycosylation, a conserved pathway in many organisms

description: Additional file 3. Ratio of intron_coverage by average_CDS_coverage, for introns with read_coverage&gt; 0.
DOI: 10.6084/m9.figshare.12082437
title: Additional file 2 of Re-annotation of the Theileria parva genome refines 53% of the proteome and uncovers essential components of N-glycosylation, a conserved pathway in many organisms

description: Additional file 2. Pairs of consecutive genes with overlap in UTR only or both UTR and CDS.
DOI: 10.6084/m9.figshare.12082431
title: Additional file 6 of A different vision of translational research in biomarker discovery: a pilot study on circulatory mitochondrial proteins as Parkinson’s disease potential biomarkers

description: Additional file 6: Supplementary Table 4. Evaluation of the total levels of the plasma proteins of Controls and Parkinson’s disease patients.
DOI: 10.6084/m9.figshare.12082437.v1
title: Additional file 2 of Re-annotation of the Theileria parva genome refines 53% of the proteome and uncovers essential components of N-glycosylation, a conserved pathway in many organisms

description: Additional file 2. Pairs of consecutive genes with overlap in UTR only or both UTR and CDS.
DOI: 10.6084/m9.figshare.12082440.v1
title: Additional file 3 of Re-annotation of the Theileria parva genome refines 53% of the proteome and uncovers essential components of N-glycosylation, a conserved pathway in many organisms

description: Additional file 3. Ratio of intron_coverage by average_CDS_coverage, for introns with read_coverage&gt; 0.
DOI: 10.6084/m9.figshare.12082425
title: Additional file 5 of A different vision of translational research in biomarker discovery: a pilot study on circulatory mitochondrial proteins as Parkinson’s disease potential biomarkers

description: Additional file 5: Supplementary Table 3. Evaluation of the total levels of the secreted proteins under control and stress conditions.
DOI: 10.6084/m9.figshare.12082431.v1
title: Additional file 6 of A different vision of translational research in biomarker discovery: a pilot study on circulatory mitochondrial proteins as Parkinson’s disease potential biomarkers

description: Additional file 6: Supplementary Table 4. Evaluation of the total levels of the plasma proteins of Controls and Parkinson’s disease patients.
DOI: 10.6084/m9.figshare.12082425.v1
title: Additional file 5 of A different vision of translational research in biomarker discovery: a pilot study on circulatory mitochondrial proteins as Parkinson’s disease potential biomarkers

description: Additional file 5: Supplementary Table 3. Evaluation of the total levels of the secreted proteins under control and stress conditions.
DOI: 10.6084/m9.figshare.12082413
title: Additional file 9 of ddRADseq-assisted construction of a high-density SNP genetic map and QTL fine mapping for growth-related traits in the spotted scat (Scatophagus argus)

description: Additional file 9 : Table S5. QTL clusters for growth-related traits in S. argus.
DOI: 10.6084/m9.figshare.12082413.v1
title: Additional file 9 of ddRADseq-assisted construction of a high-density SNP genetic map and QTL fine mapping for growth-related traits in the spotted scat (Scatophagus argus)

description: Additional file 9 : Table S5. QTL clusters for growth-related traits in S. argus.
DOI: 10.6084/m9.figshare.12082395
title: Additional file 7 of ddRADseq-assisted construction of a high-density SNP genetic map and QTL fine mapping for growth-related traits in the spotted scat (Scatophagus argus)

description: Additional file 7 : Table S4. Estimation of the expected genetic distance of S. argus linkage maps.
DOI: 10.6084/m9.figshare.12082395.v1
title: Additional file 7 of ddRADseq-assisted construction of a high-density SNP genetic map and QTL fine mapping for growth-related traits in the spotted scat (Scatophagus argus)

description: Additional file 7 : Table S4. Estimation of the expected genetic distance of S. argus linkage maps.
DOI: 10.6084/m9.figshare.12082386
title: Additional file 4 of ddRADseq-assisted construction of a high-density SNP genetic map and QTL fine mapping for growth-related traits in the spotted scat (Scatophagus argus)

description: Additional file 4 : Table S3. Statistic information of the sex-specific genetic maps of S. argus.
DOI: 10.6084/m9.figshare.12082383
title: Additional file 3 of ddRADseq-assisted construction of a high-density SNP genetic map and QTL fine mapping for growth-related traits in the spotted scat (Scatophagus argus)

description: Additional file 3 : Table S2. Segregation patterns of heterozygotic SNP locus in the mapping population of S. argus.
DOI: 10.6084/m9.figshare.12082386.v1
title: Additional file 4 of ddRADseq-assisted construction of a high-density SNP genetic map and QTL fine mapping for growth-related traits in the spotted scat (Scatophagus argus)

description: Additional file 4 : Table S3. Statistic information of the sex-specific genetic maps of S. argus.
DOI: 10.6084/m9.figshare.12082383.v1
title: Additional file 3 of ddRADseq-assisted construction of a high-density SNP genetic map and QTL fine mapping for growth-related traits in the spotted scat (Scatophagus argus)

description: Additional file 3 : Table S2. Segregation patterns of heterozygotic SNP locus in the mapping population of S. argus.
DOI: 10.6084/m9.figshare.12082368
title: Additional file 1 of ddRADseq-assisted construction of a high-density SNP genetic map and QTL fine mapping for growth-related traits in the spotted scat (Scatophagus argus)

description: Additional file 1 : Table S1. The statistics of eight growth-related traits of S. argus full-sib family. BW: body weight; TL: total length; BL: body length; BH: body height; PD: pre-dorsal length; PA: pre-anal length; HL: head length; CPH: caudal peduncle height; SD: standard deviation; CV: coefficient of variation.
DOI: 10.6084/m9.figshare.12082368.v1
title: Additional file 1 of ddRADseq-assisted construction of a high-density SNP genetic map and QTL fine mapping for growth-related traits in the spotted scat (Scatophagus argus)

description: Additional file 1 : Table S1. The statistics of eight growth-related traits of S. argus full-sib family. BW: body weight; TL: total length; BL: body length; BH: body height; PD: pre-dorsal length; PA: pre-anal length; HL: head length; CPH: caudal peduncle height; SD: standard deviation; CV: coefficient of variation.
DOI: 10.6084/m9.figshare.12082305
title: Additional file 3 of OffsampleAI: artificial intelligence approach to recognize off-sample mass spectrometry images

description: Additional file 3 : Supplementary Data D1-D5: D1: “Supplementary methods and results.pdf”. D2: “Interactive tagging of ion images using web app.mov”, video of a tagger using the TagOff web app. D3: “Gold standard datasets.csv”, metadata of 87 public datasets from METASPACE selected for the gold standard. D4: “DHB matrix clusters frequencies.csv”, results of annotation of 31 gold standard datasets acquired using the MALDI DHB matrix and positive ion mode and off-sample recognition for DHB matrix clusters generated according to a combinatorial model. D5: “DESI offsample ions frequencies.csv”, a file showing for each molecular formula the number of DESI imaging datasets from the gold standard where ions with such molecular formula were classified as off-sample.
DOI: 10.6084/m9.figshare.12082305.v1
title: Additional file 3 of OffsampleAI: artificial intelligence approach to recognize off-sample mass spectrometry images

description: Additional file 3 : Supplementary Data D1-D5: D1: “Supplementary methods and results.pdf”. D2: “Interactive tagging of ion images using web app.mov”, video of a tagger using the TagOff web app. D3: “Gold standard datasets.csv”, metadata of 87 public datasets from METASPACE selected for the gold standard. D4: “DHB matrix clusters frequencies.csv”, results of annotation of 31 gold standard datasets acquired using the MALDI DHB matrix and positive ion mode and off-sample recognition for DHB matrix clusters generated according to a combinatorial model. D5: “DESI offsample ions frequencies.csv”, a file showing for each molecular formula the number of DESI imaging datasets from the gold standard where ions with such molecular formula were classified as off-sample.
DOI: 10.6084/m9.figshare.12082245
title: Additional file 3 of Comparison of serum protein profiles between major depressive disorder and bipolar disorder

description: Additional file 3. IPA Canonical Pathway and IPA Diseases & Functions.
DOI: 10.6084/m9.figshare.12082239
title: Additional file 2 of Comparison of serum protein profiles between major depressive disorder and bipolar disorder

description: Additional file 2. Major protein IDs and full protein IDs of the differentially-expressed proteins. (Protein IDs and majority protein IDs).
DOI: 10.6084/m9.figshare.12082245.v1
title: Additional file 3 of Comparison of serum protein profiles between major depressive disorder and bipolar disorder

description: Additional file 3. IPA Canonical Pathway and IPA Diseases & Functions.
DOI: 10.6084/m9.figshare.12082239.v1
title: Additional file 2 of Comparison of serum protein profiles between major depressive disorder and bipolar disorder

description: Additional file 2. Major protein IDs and full protein IDs of the differentially-expressed proteins. (Protein IDs and majority protein IDs).
DOI: 10.6084/m9.figshare.12082233
title: Additional file 1 of Comparison of serum protein profiles between major depressive disorder and bipolar disorder

description: Additional file 1. List of 268 proteins subjected to statistical analysis. (Protein IDs and majority protein IDs).
DOI: 10.6084/m9.figshare.12082233.v1
title: Additional file 1 of Comparison of serum protein profiles between major depressive disorder and bipolar disorder

description: Additional file 1. List of 268 proteins subjected to statistical analysis. (Protein IDs and majority protein IDs).
DOI: 10.6084/m9.figshare.12082215
title: Additional file 3 of Impact of lignans in oilseed mix on gut microbiome composition and enterolignan production in younger healthy and premenopausal women: an in vitro pilot study

description: Additional file 3: Table S1. Results of adonis and ANOSIM statistics applied to weighted and unweighted UniFrac distance-based ordination (related to Fig. 4 and Additional file 2: Fig. S2). PD: premenopausal donor; YD: younger donor.
DOI: 10.6084/m9.figshare.12082215.v1
title: Additional file 3 of Impact of lignans in oilseed mix on gut microbiome composition and enterolignan production in younger healthy and premenopausal women: an in vitro pilot study

description: Additional file 3: Table S1. Results of adonis and ANOSIM statistics applied to weighted and unweighted UniFrac distance-based ordination (related to Fig. 4 and Additional file 2: Fig. S2). PD: premenopausal donor; YD: younger donor.
DOI: 10.6084/m9.figshare.12082131
title: Data and codes of Indoor mapping and modeling by parsing floor plan images

description: <b>1-WID512_ROTATE.tar.gz</b>This package is the training and inference data of CVC-FP for Mask RCNN. Please visit https://github.com/facebookresearch/Detectron to check the training and inference guidance.<br><b>5_folds_result.tar.gz</b>This package is results of 5-fold cross validation datasets. The results are stored as shapefiles and named after the name of floor plan images.<br><b>submitted_code.7z & test_data.tar.gz</b>These two packages are the codes and the corresponding test data. Please unpack them and check the guidance of readme.md.
DOI: 10.6084/m9.figshare.12082134
title: Results of 5-fold cross validation on CVC-FP

description: This link provides the results of the 5-fold cross-validation dataset. The results are stored as shapefiles and named after the name of floor plan images.
DOI: 10.6084/m9.figshare.12082038
title: Humans achieved optimal motor-timing decisions through voluntary risk-return control

description: data file for peer review in scientific reports
DOI: 10.6084/m9.figshare.12082035
title: The codon usage pattern of the novel coronavirus

description: <b> </b>The current outbreak of a novel coronavirus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) is spreading rapidly across the whole world. The World Health Organization has declared the coronavirus diseases (COVID-19) to be a global pandemic. COVID-19 is milder, less fatal than SARS and MERS, but SARS-CoV-2 poses more serious threats to public health, because it is highly contagious and has a high potential of causing severe-acute, life-threatening pneumonia. Here we analyzed the similarities of codon usages between humans and different viruses, including human immunodeficiency virus (HIV), highly pathogenic avian influenza (HPAI), and coronavirus (CoV). The codon usages of HPAIs are highly similar to that of humans. In contrast, the codon usage of HIVs and CoVs is less and the codon usage of SARS-CoV-2 is the least similar to that of humans among all viruses tested. Besides, human-preferred codons are adopted to substitute less-preferred ones in SARS-CoV; in SARS-CoV-2, however, human-preferred codons are replaced by less-preferred ones. The unique codon usage pattern suggests that SARS-CoV-2 was probably formed by evolving in an unusual intermediate host over a long period, in which its codon usage became drastically different from that of humans and those of other pathogenic viruses. Moreover, its pathogenicity is weakened compared with SARS-CoV, but it becomes more potent and may gain higher potentials in the future. Therefore, there is an urgent need to block the transmission routes among humans, search for the origin and intermediate hosts of the coronaviruses, and prevent any future outbreaks.<br>
DOI: 10.6084/m9.figshare.12082038.v1
title: Humans achieved optimal motor-timing decisions through voluntary risk-return control

description: data file for peer review in scientific reports