cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23808354.v1
title: A network pharmacology approach to elucidate the anti-inflammatory effects of ellagic acid

description: Ellagic acid (EA) is a naturally occurring polyphenolic compound found in various fruits and vegetables like strawberries, raspberries, pomegranates, and nuts such as pecans and walnuts. With its antioxidant properties, EA has shown potential health benefits, although further research is necessary to fully comprehend its effects, mechanisms, and safe and effective application as a complementary medicine. Notably, there is accumulating evidence of EA's anti-inflammatory effects; however, the precise underlying mechanism remains unclear. To investigate the anti-inflammatory properties of EA, a network pharmacology approach was employed. The study identified 52 inflammation-related targets of EA and revealed significant signaling pathways and relevant diseases associated with inflammation through GO and KEGG analysis. Furthermore, topological analysis identified 10 important targets, including AKT1, VEGFA, TNF, MAPK3, ALB, SELP, MMP9, MMP2, PTGS2, and ICAM1. Molecular docking and molecular dynamics simulations were conducted, indicating that AKT1, PTGS2, VEGFA, and MAPK3 are the most likely targets of EA, as evidenced by their molecular mechanics Poisson-Boltzmann surface area binding energy calculations. In summary, this study not only confirmed the anti-inflammatory effects of EA observed in previous research but also identified the most probable targets of EA. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.23741638
title: Construction of a HIV-1 subtype C 3D model using homology modeling and in-silico docking, molecular dynamics simulation, and MM-GBSA calculation of second-generation HIV-1 maturation inhibitor(s)

description: Maturation inhibitors (MIs) efficiently block HIV-1 maturation by inhibiting the cleavage of the capsid protein and spacer peptide 1 (CA-SP1) leading to the production of immature and non-infectious virus particles. We have previously reported that second-generation MIs were more potent than bevirimat (BVM) against HIV-1 subtype C. In-silico studies on interaction of with BVM and their analogs have been limited to HIV-1 subtype B(5I4T) due to lack of an available 3D structure for HIV-1 subtype C virus. In our current study, we have developed a 3D model of HIV-1C Gag CA-SP1 region using protein homology modeling with HIV-1 subtype B(514T) as a template. The HIV-1 C homology model generated was extensively validated using several online tools and served as a template to perform molecular docking studies with eight well-characterized MIs. The docked complex of HIV-1C and all nine MIs was subjected to molecular dynamics simulation for 100 ns using AMBER and binding free energy calculations were done using MM-GBSA. Based on our data, CV8611 exhibited highest binding energy of −6.5 Kcal/mol among all BVM analogs. CV8611 formed strong interactions with Gly222 and Met235 of HIV-1C Gag CA-SP1 during MD simulation and remained intact. The root mean square deviation and root mean square fluctuation values of the complex were stable during the simulations. Our study is the first to report construction and validation of 3D model for the HIV-1C Gag CA-SP1, which could serve as a crucial tool in the structure-aided design of novel and broadly acting maturation inhibitors. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.23741638.v1
title: Construction of a HIV-1 subtype C 3D model using homology modeling and in-silico docking, molecular dynamics simulation, and MM-GBSA calculation of second-generation HIV-1 maturation inhibitor(s)

description: Maturation inhibitors (MIs) efficiently block HIV-1 maturation by inhibiting the cleavage of the capsid protein and spacer peptide 1 (CA-SP1) leading to the production of immature and non-infectious virus particles. We have previously reported that second-generation MIs were more potent than bevirimat (BVM) against HIV-1 subtype C. In-silico studies on interaction of with BVM and their analogs have been limited to HIV-1 subtype B(5I4T) due to lack of an available 3D structure for HIV-1 subtype C virus. In our current study, we have developed a 3D model of HIV-1C Gag CA-SP1 region using protein homology modeling with HIV-1 subtype B(514T) as a template. The HIV-1 C homology model generated was extensively validated using several online tools and served as a template to perform molecular docking studies with eight well-characterized MIs. The docked complex of HIV-1C and all nine MIs was subjected to molecular dynamics simulation for 100 ns using AMBER and binding free energy calculations were done using MM-GBSA. Based on our data, CV8611 exhibited highest binding energy of −6.5 Kcal/mol among all BVM analogs. CV8611 formed strong interactions with Gly222 and Met235 of HIV-1C Gag CA-SP1 during MD simulation and remained intact. The root mean square deviation and root mean square fluctuation values of the complex were stable during the simulations. Our study is the first to report construction and validation of 3D model for the HIV-1C Gag CA-SP1, which could serve as a crucial tool in the structure-aided design of novel and broadly acting maturation inhibitors. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.23773594
title: AndroPred: an artificial intelligence-based model for predicting androgen receptor inhibitors

description: Androgen receptor (AR), a steroid receptor, plays a pivotal role in the pathogenesis of prostate cancer (PCa). AR controls the transcription of genes that help cells avoid apoptosis and proliferate, thereby contributing to the development of PCa. Understanding AR molecular mechanisms has led to the development of newer drugs that inhibit androgen production enzymes or block ARs. The FDA has approved a small number of AR-inhibiting drugs for use in PCa thus far, as the identification of novel AR inhibitors is difficult, expensive, time-consuming, and labor-intensive. To accelerate the process, artificial intelligence (AI) algorithms were employed to predict AR inhibitors using a dataset of 2242 compounds. Four machine learning (ML) and deep learning (DL) algorithms were used to train different prediction models based on molecular descriptors (1D, 2D, and molecular fingerprints). The DL-based prediction model outperformed the other trained models with accuracies of 92.18% and 93.05% on the training and test datasets, respectively. Our findings highlight the potential of DL, particularly the DNN model, as an effective approach for predicting AR inhibitors, which could significantly streamline the process of identifying novel AR inhibitors in PCa drug discovery. Further validation of these models using experimental assays and prospective testing of newly designed compounds would be valuable to confirm their predictive power and applicability in practical drug discovery settings. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.23773594.v1
title: AndroPred: an artificial intelligence-based model for predicting androgen receptor inhibitors

description: Androgen receptor (AR), a steroid receptor, plays a pivotal role in the pathogenesis of prostate cancer (PCa). AR controls the transcription of genes that help cells avoid apoptosis and proliferate, thereby contributing to the development of PCa. Understanding AR molecular mechanisms has led to the development of newer drugs that inhibit androgen production enzymes or block ARs. The FDA has approved a small number of AR-inhibiting drugs for use in PCa thus far, as the identification of novel AR inhibitors is difficult, expensive, time-consuming, and labor-intensive. To accelerate the process, artificial intelligence (AI) algorithms were employed to predict AR inhibitors using a dataset of 2242 compounds. Four machine learning (ML) and deep learning (DL) algorithms were used to train different prediction models based on molecular descriptors (1D, 2D, and molecular fingerprints). The DL-based prediction model outperformed the other trained models with accuracies of 92.18% and 93.05% on the training and test datasets, respectively. Our findings highlight the potential of DL, particularly the DNN model, as an effective approach for predicting AR inhibitors, which could significantly streamline the process of identifying novel AR inhibitors in PCa drug discovery. Further validation of these models using experimental assays and prospective testing of newly designed compounds would be valuable to confirm their predictive power and applicability in practical drug discovery settings. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.26636160.v1
title: Additional file 1 of Laboratory tests to understand tephra sliding behaviour on roofs

description: Additional file 1: Supplementary material. Sliding test results.
DOI: 10.15468/dl.wmw796
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.650227 -34.354519, 148.650227 -34.359011, 148.656964 -34.359011, 148.656964 -34.354519, 148.650227 -34.354519)), ((148.656964 -34.359011, 148.656964 -34.361257, 148.65921 -34.361257, 148.65921 -34.363502, 148.661456 -34.363502, 148.661456 -34.367994, 148.668193 -34.367994, 148.668193 -34.361257, 148.672685 -34.361257, 148.672685 -34.354519, 148.65921 -34.354519, 148.65921 -34.359011, 148.656964 -34.359011)), ((148.668193 -34.367994, 148.668193 -34.37024, 148.672685 -34.37024, 148.672685 -34.367994, 148.668193 -34.367994)))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071003-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.24515905.v1
title: Additional file 1 of Subcellular trafficking and transcytosis efficacy of different receptor types for therapeutic antibody delivery at the blood‒brain barrier

description: Additional file 1.
DOI: 10.6084/m9.figshare.26768200
title: Liriopes Radix nanovesicles protein testing

description: Identification of LRNVs proteins under Asparagaceae using the Uniprot Protein Database (https://www.uniprot.org/). Protein collections were detected from the database to construct Venn plots, cluster heat maps, and principal component analysis plots. At the same time, the proteins were annotated according to the COG (Clusters of Orthologous Groups) database, Gene Ontology (GO) database (http://www.geneontology.org/), GO Slim analysis, and KEGG (http://www.genome.jp/kegg) database to obtain their function s and enrichment pathways
DOI: 10.6084/m9.figshare.26768200.v1
title: Liriopes Radix nanovesicles protein testing

description: Identification of LRNVs proteins under Asparagaceae using the Uniprot Protein Database (https://www.uniprot.org/). Protein collections were detected from the database to construct Venn plots, cluster heat maps, and principal component analysis plots. At the same time, the proteins were annotated according to the COG (Clusters of Orthologous Groups) database, Gene Ontology (GO) database (http://www.geneontology.org/), GO Slim analysis, and KEGG (http://www.genome.jp/kegg) database to obtain their function s and enrichment pathways
DOI: 10.15468/dl.8pyr3e
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.030386 -34.356765, 148.030386 -34.359011, 148.032632 -34.359011, 148.032632 -34.356765, 148.030386 -34.356765)), ((148.032632 -34.359011, 148.032632 -34.361257, 148.037124 -34.361257, 148.037124 -34.359011, 148.032632 -34.359011)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071004-240626123714530/datasets/export for details.
DOI: 10.6084/m9.figshare.24516079
title: Additional file 2 of PPARG is a potential target of Tanshinone IIA in prostate cancer treatment: a combination study of molecular docking and dynamic simulation based on transcriptomic bioinformatics

description: Additional file 2. Tanshinone IIA targets predicted by Pharmmapper.
DOI: 10.17632/g4vgyn8n39.1
title: APK_AIM_Replication_File

description: This zip file contains the replication package for "Do Personal Taxes Affect Investment Decisions and Stock Returns? by Alexander P. Kontoghiorghes.
DOI: 10.6084/m9.figshare.26636286.v1
title: Additional file 3 of PPARG is a potential target of Tanshinone IIA in prostate cancer treatment: a combination study of molecular docking and dynamic simulation based on transcriptomic bioinformatics

description: Additional file 3. Transcription factors predicted to be interfered with Tanshinone IIA.
DOI: 10.6084/m9.figshare.26636727
title: Additional file 5 of The DNA barcode identification of Dalbergia odorifera T. Chen and Dalbergia tonkinensis Prain

description: Supplementary Material 5
DOI: 10.5281/zenodo.13271782
title: Triple Negative Breast Cancer TMA IMC

description: Triple Negative Breast Cancer patient Tissue Microarray (TMA) Imaging Mass Cytometry (IMC).

Standard IMC MCD files with de-IDed patient data.
DOI: 10.25346/s6/ylxabh/xs5n4i
title: PSD_Then_EFlux_1_2_v8.m
DOI: 10.15468/dl.8968wx
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((146.375232 -34.359011, 146.375232 -34.361257, 146.379724 -34.361257, 146.379724 -34.359011, 146.375232 -34.359011)), ((146.379724 -34.361257, 146.379724 -34.363502, 146.384215 -34.363502, 146.384215 -34.359011, 146.38197 -34.359011, 146.38197 -34.361257, 146.379724 -34.361257)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071005-240626123714530/datasets/export for details.
DOI: 10.25346/s6/ylxabh/zc1nb3
title: Histogram_Radial_PSD_in_L_Paper_Figure_v7.m
DOI: 10.25346/s6/ylxabh/0vlfb3
title: PSD_Then_EFlux_4_v4.m
DOI: 10.25346/s6/ylxabh/okt3b2
title: Search_for_PSD_Peaks_v1point6.m
DOI: 10.6084/m9.figshare.26636634.v1
title: Additional file 8 of Integrative single-cell RNA-seq analysis of vascularized cerebral organoids

description: Additional file 8: Table S2. List of genes altered by vascularization. No cut-off p-values are used in this table.
DOI: 10.6084/m9.figshare.26636649
title: Additional file 13 of Integrative single-cell RNA-seq analysis of vascularized cerebral organoids

description: Additional file 13: Table S5. Differentially expressed genes in the fetal brain of endothelial populations. No cut-off p-values are used in this table.
DOI: 10.15468/dl.pcc53t
title: Occurrence Download

description: A dataset containing 16146 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Taxonomy and distribution of ecosystem types: implementation of ecosystemology principles"
 ]
}

 The dataset includes 16146 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071006-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26635665.v1
title: Additional file 1 of Non-coding RNA-mediated endothelial-to-mesenchymal transition in human diabetic cardiomyopathy, potential regulation by DNA methylation

description: Additional file 1: Table S1. Complete patient data.
DOI: 10.6084/m9.figshare.26636415
title: Additional file 4 of Alterations to DNA methylation patterns induced by chemotherapy treatment are associated with negative impacts on the olfactory pathway

description: Additional file 4. Association between chemotherapy and DNA methylation in promoter regions (pre- and post-chemotherapy paired samples in 125 breast cancer patients). Presented here are associations that reached statistical significance at a Bonferroni threshold p-value of &lt;1.21e-6. Standard error = stdev.unscaled * s2.post.
DOI: 10.15468/dl.w24cr7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((146.788459 -34.359011, 146.788459 -34.361257, 146.792951 -34.361257, 146.792951 -34.359011, 146.788459 -34.359011)), ((146.792951 -34.361257, 146.792951 -34.363502, 146.795197 -34.363502, 146.795197 -34.361257, 146.792951 -34.361257)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071007-240626123714530/datasets/export for details.
DOI: 10.6084/m9.figshare.26636430.v1
title: Additional file 9 of Alterations to DNA methylation patterns induced by chemotherapy treatment are associated with negative impacts on the olfactory pathway

description: Additional file 9. Association between chemotherapy and DNA methylation in 525,100 CpG probes in 1,808 breast cancer patients with blood specimens (1,066 with chemotherapy and 742 without chemotherapy). Presented here are associations that reached statistical significance at a Bonferroni threshold p-value (p&lt;9.52e-8) in either unadjusted analysis or after adjustments for batch, immune cell content (LUMP), cell types, year of breast cancer diagnosis, and ethnicity. Standard error = stdev.unscaled * s2.post.
DOI: 10.6084/m9.figshare.26636439.v1
title: Additional file 12 of Alterations to DNA methylation patterns induced by chemotherapy treatment are associated with negative impacts on the olfactory pathway

description: Additional file 12. Association between chemotherapy and DNA methylation in 40,271 promoter regions in 337 breast cancer patients with saliva specimens (207 treated and 130 not treated with chemotherapy). Presented here are associations that reached statistical significance at a Bonferroni threshold p-value (p&lt;1.24e-6) in either unadjusted analysis or after adjustments for batch, immune cell content (LUMP), year of breast cancer diagnosis, and ethnicity. Standard error = stdev.unscaled * s2.post.
DOI: 10.15468/dl.rj35jp
title: Occurrence Download

description: A dataset containing 16146 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Taxonomy and distribution of ecosystem types: implementation of ecosystemology principles"
 ]
}

 The dataset includes 16146 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071008-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26636835
title: Additional file 2 of Non-target screening of surface water samples to identify exposome-related pollutants: a case study from Luxembourg

description: Additional file 2: Table S1. Sampling sites with weblinks. Table S2. Feature finding optimization results. Table S3. Number of 2, 3a and 3b identifications. Table S4. Number of positive and negative identifications. Table S5. Tentatively identified chemicals per month. Table S6. ClassyFire results. Table S7. PubChemLite classifications. Table S8. AGE monitoring comparison. Table S9. Krier et al. (pesticides) comparison. Table S10. Singh et al. (pharmaceuticals) comparison. Table S11. Chiers WWTP Petange comparison (SMILES). Table S12. Chiers results (SMILES) all months. Table S13. List of chemicals with high occurrence in the 34 months analysed, and not currently monitored by AGE. Table S14. European watchlist 2022 comparison.
DOI: 10.6084/m9.figshare.26636442.v1
title: Additional file 13 of Alterations to DNA methylation patterns induced by chemotherapy treatment are associated with negative impacts on the olfactory pathway

description: Additional file 13. Gene set enrichment analysis of Gene Ontology (GO) biological processes from results of unadjusted and adjusted models, by specimen type (blood or saliva).
DOI: 10.15468/dl.xwm2ap
title: Occurrence Download

description: A dataset containing 1644 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "TaxonKey is Lantana camara L."
 ]
}

 The dataset includes 1644 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071009-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6qf3tw
title: Occurrence Download

description: A dataset containing 98 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Nudibranchia de la colección del Museo de La Plata, Argentina"
 ]
}

 The dataset includes 98 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071010-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26636802.v1
title: Additional file 3 of A newly identified glycosyltransferase AsRCOM provides resistance to purple curl leaf disease in agave

description: Supplementary Material 3: Supplementary Table S3. The modules of RNA-seq data divided by WGCNA
DOI: 10.6084/m9.figshare.26636919
title: Additional file 1 of An individualized Bayesian method for estimating genomic variants of hypertension

description: Additional file 1. The top 188 SNPs ranked by p-value. Corresponding columns include rsID, CHR, gene, MAF, p-value,Ms, GPP, Ms,r, Rank_p-value, Rank_Ms, and Rank_Ms,r.
DOI: 10.6084/m9.figshare.26636925
title: Additional file 3 of An individualized Bayesian method for estimating genomic variants of hypertension

description: Additional file 3. The top 188 SNPs ranked by Ms,r. Corresponding columns include rsID, Chromosome (CHR), gene, MAF, p-value, Ms, GPP, Ms,r,Rank_p-value, Rank_Ms, and Rank_Ms,r.
DOI: 10.6084/m9.figshare.26636925.v1
title: Additional file 3 of An individualized Bayesian method for estimating genomic variants of hypertension

description: Additional file 3. The top 188 SNPs ranked by Ms,r. Corresponding columns include rsID, Chromosome (CHR), gene, MAF, p-value, Ms, GPP, Ms,r,Rank_p-value, Rank_Ms, and Rank_Ms,r.
DOI: 10.15468/dl.phxk84
title: Occurrence Download

description: A dataset containing 785 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Colección de Mamíferos Marinos del Centro Nacional Patagónico"
 ]
}

 The dataset includes 785 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071012-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26636928.v1
title: Additional file 4 of An individualized Bayesian method for estimating genomic variants of hypertension

description: Additional file 4. The Information gain values for the top 188 SNPs ranked by IBI and GWAS respectively, as well as 188 SNPs selected at random. The method column specifies the method (such as IBI or GWAS) used to identify the SNPs.
DOI: 10.15468/dl.awtnrc
title: Occurrence Download

description: A dataset containing 2355 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Colección Ictiológica del CENPAT-CONICET"
 ]
}

 The dataset includes 2355 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071013-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.