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1,260 results for “Pharmacology”
PharmaCoNER corpus: gold standard annotations of Pharmacological Substances, Compounds and proteins in Spanish clinical case reports
<p><strong>Intro:</strong></p><p>The PharmaCoNER corpus (divided into train, dev and test) is a Gold Standard manually annotated dataset used for the the PharmaCoNER shared task posed at BIONLP-ST (at EMNLP). In addition, we include here the PharmaCoNER background set. It contains the train, development and test sets of the two subtasks (subtask-1 and subtask-2) with Gold Standard annotations. In addition, it contains the documents of the background set, without annotations.</p><p>The PharmaCoNER corpus consists of:</p><ul><li>Manually classified clinical case sections derived from Open access Spanish medical publications, named the Spanish Clinical Case Corpus (SPACCC).</li><li>It was manually selected by a practicing oncologist and revised by a clinical documentalist to assure that records were relevant/representative and resembled structure and content relevant to process clinical records.</li><li>The final corpus: 1000 clinical cases 16,504 sentences</li><li>The corpus contains a total of 396,988 words, with an average of 396.2 words per clinical case.</li><li>It covers a range of medical disciplines including oncology, urology, cardiology, pneumology or infections diseases, etc.</li><li>The corpus has been annotated at the mention level by experts in medicinal chemistry and pharmacology following a granular annotation scheme covering four mention types:<ul><li><i>Entity type 1 (NORMALIZABLES)</i>: mentions of chemicals that can be manually normalized to a unique concept identifier (primarily SNOMED-CT).</li><li><i>Entity type 2 (NO_NORMALIZABLES)</i>: mentions of chemicals that could not be normalized manually to a unique concept identifier.</li><li><i>Entity type 3 (PROTEINAS)</i>: mentions of proteins/genes following an adaptation of the BioCreative GPRO track annotation guidelines (includes peptides, peptide hormones & antibodies).</li><li><i>Entity type 4 (UNCLEAR )</i>: cases of general substance class mentions of clinical relevance, including certain pharmaceutical formulations, general treatments, chemotherapy programs, and vaccines.</li><li>Mentions class "<i>UNCLEAR</i>" (not evaluated for the PharmaCoNER track)</li></ul></li></ul><p> </p><p> </p><p><strong>Please, cite: </strong></p><p>A. G. Agirre, M. Marimon, A. Intxaurrondo, O. Rabal, M. Villegas, M. Krallinger, Pharmaconer: Pharmacological substances, compounds and proteins named entity recognition track, in: Proceedings of The 5th Workshop on BioNLP Open Shared Tasks, 2019, pp. 1–10.</p><p> </p><p><strong>Annotation quality</strong></p><p>Inter-annotator agreement: 93% for annotation, 73% for mapping.</p><p>For more information, see the <a href="https://paperswithcode.com/paper/pharmaconer-pharmacological-substances">paper</a>.</p><p> </p><p><strong>Format</strong></p><p>For subtask 1 annotations are distributed in <i>Brat</i> format. (More info at Brat webpage https://brat.nlplab.org/standoff.html)</p><p>For subtask-2, codes are associated with each document are given in a <i>TSV</i> file with the following columns: </p><blockquote><p>filename code</p></blockquote><p> </p><p><strong>Shared task goal:</strong></p><p>In the two subtasks, the goal is to predict the annotations of the test files (either the ANN files or the TSV with the codes) given only the plain text files. </p><p> </p><p><strong>Resources:</strong></p><ul><li><a href="https://temu.bsc.es/pharmaconer/"><strong>Web</strong></a></li><li><a href="https://www.aclweb.org/anthology/D19-5701.pdf"><strong>Citation</strong></a><strong>: </strong>A. G. Agirre, M. Marimon, A. Intxaurrondo, O. Rabal, M. Villegas, M. Krallinger, Pharmaconer: Pharmacological substances, compounds and proteins named entity recognition track, in: Proceedings of The 5th Workshop on BioNLP Open Shared Tasks, 2019, pp. 1–10.</li><li><a href="https://doi.org/10.5281/zenodo.4271908"><strong>Silver Standard corpus</strong></a></li><li><a href="https://doi.org/10.5281/zenodo.3763276"><strong>Annotation guidelines</strong></a></li><li><a href="https://github.com/TeMU-BSC/PharmaCoNER-Tagger"><strong>PharmaCoNER tagger</strong></a></li><li><a href="https://www.youtube.com/watch?v=B3ZzJl5OMkY"><strong>Youtube video(general setting)</strong></a></li><li><a href="https://www.slideshare.net/MartinKrallinger/pharmaconer-pharmacological-substances-compounds-and-proteins-named-entity-recognition-track-at-bionlpost-workshop-november-4-skycity-rm-2-hong-kong-emnlp2019"><strong>Slides PharmacoNER overview talk at BIONLP-ST / EMNLP </strong></a></li></ul><p>For further information, please visit <a href="https://temu.bsc.es/pharmaconer/">https://temu.bsc.es/pharmaconer/</a> or email us at encargo-pln-life@bsc.es</p><p>Copyright (c) 2018 Secretaría de Estado para el Avance Digital (SEAD)</p><p> </p><p><strong>License</strong></p><p>This work is licensed under a <a href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.</p><p> </p><p><strong>Contact</strong></p><p>If you have any questions or suggestions, please contact us at:</p><p><br>- Martin Krallinger (<krallinger [dot] martin [at] gmail [dot] com>)</p><p><strong>Additional resources and corpora</strong></p><p>If you are interested in PharmaCoNER, you might want to check out these corpora and resources:</p><ul><li><a href="https://zenodo.org/records/7614764">DisTEMIST</a> (Corpus of disease mentions and normalization to SNOMED CT, same document collection)</li><li><a href="https://zenodo.org/records/8224056">MedProcNER </a>(Corpus of clinical procedure mentions and normalization to SNOMED CT, same document collection)</li><li><a href="https://zenodo.org/records/8413866">SympTEMIST</a> (Corpus of symptoms, signs and findings mentions and normalization, same document collection)</li><li><a href="https://zenodo.org/records/7116201">MEDDOPROF</a> (Corpus of mentions of professions, occupations and working status and normalization, different document collection with some overlapping documents)</li><li><a href="https://zenodo.org/records/8403498">MEDDOPLACE</a> (Corpus of mentions of place-related entity mentions, including departments, nationalities or patient movements etc.. and normalization, different document collection with some overlapping documents)</li><li><a href="https://zenodo.org/records/4279323">MEDDOCAN</a> (Corpus of mentions of Personal Health Identifiers (PHI), modified synthetic verions of the document collection)</li><li><a href="https://zenodo.org/records/3978041">CANTEMIST</a> (Corpus of cancer tumor morphology mentions and normalization, different document collection)</li><li><a href="https://zenodo.org/records/3837305">CodiESp</a> (Corpus of clinical case reportes with assigned clinical codes from ICD10, Spanish version, same document collection)</li><li><a href="https://zenodo.org/records/7684093">LivingNER</a> (Corpus of mentions of species, including human/family members, pathogens, food, etc.. and normalization to NCBI Taxonomy, different document collection with some overlapping documents)</li><li><a href="https://zenodo.org/records/2560344">SPACCC-POS</a> (Corpus of clinical case reports in Spanish annotated with POS-tags, same document collection)</li><li><a href="https://zenodo.org/records/2560338">SPACCC-TOKEN</a> (Corpus of clinical case reports in Spanish annotated with token-tags (word mention boundaries), same document collection)</li><li><a href="https://zenodo.org/records/2560338">SPACCC-SPLIT</a> (Corpus of clinical case reports in Spanish annotated with sentence boundary-tags, same document collection)</li><li><a href="https://zenodo.org/records/5602914">MESINESP-2</a> (Corpus of manually indexed records with DeCS /MeSH terms comprising scientific literature abstracts, clinical trials, and patent abstracts, different document collection)</li></ul>
ePharmaLib: A Versatile Library of e-Pharmacophores to Address Small-Molecule (Poly-)Pharmacology
<p><em><strong>The peer-reviewed publication for this dataset has now been published in Journal of Chemical Information and Modeling, and can be accessed here: <a href="https://doi.org/10.3390/epidemiologia2030024">https://doi.org/10.1021/acs.jcim.1c00135</a>. Please cite this when using the dataset.</strong></em></p> <p><em>Reverse pharmacophore screening (parallel screening) is an efficient and cost-effective computational method used to study the polypharmacology of drugs. To this end, we created ePharmaLib: a collection of 15,148 energetically optimized, structure-based pharmacophores (e-pharmacophores) , with 3 to 8 features constituting 12.6%, 17.9%, 20.9%, 17.1%, 10.6% and 20.9%, respectively. The pharmacophores were generated from the 3D macromolecular structures of druggable proteins in complex with diverse ligands, retrieved from the sc-PDB database (<a href="http://bioinfo-pharma.u-strasbg.fr/scPDB/">http://bioinfo-pharma.u-strasbg.fr/scPDB/</a>). ePharmaLib can either be used with the Schrödinger’s PHASE program (<a href="https://www.schrodinger.com/products/phase">https://schrodinger.com/products/phase</a>) or PHARAO, also known as Align-it (<a href="https://silicos-it.be.s3-website-eu-west-1.amazonaws.com/software/align-it/1.0.4/align-it.html">https://silicos-it.be.s3-website-eu-west-1.amazonaws.com/software/align-it/1.0.4/align-it.html</a>). Designed for drug discovery research, this ready-to-use library could dramatically expedite drug discovery by revealing novel molecular interactions of drugs in an efficient and cost-effective manner.</em></p>
TPE-MI reveals proteome remodelling in response to pharmacological stimuli
<p>Dataset contains raw and preprocessed data for fluorescence and proteomic studies respectively. In each case, protein foldedness was probed using thiol reactivity. The raw mass spectrometry proteomics data have also been deposited to the ProteomeXchange Consortium via the PRIDE partner repository, with the dataset identifiers PXD033152.</p>
FIG, 1. John William Daly (1933–2008) on the upper Río San Juan. This paper is dedicated to John Daly, our late friend and colleague, who helped collect three of the new species here described. In addition to his globally acclaimed discoveries in chemistry and pharmacology, John was an accomplished field herpetologist who contributed importantly to the systematics and natural history of dendrobatoid frogs (see Grant et al., 2006; Myers, 2009). This photograph shows John at age 37, with the upper Río San Juan behind him and branches overhead of a madroño tree (probably Garcinia magnifolia, syn. Rheedia chocoensis, Clusiaceae). When in South America, John was never far from a dendrobatid frog—this time, in the tree above his head, a tiny, undescribed semiarboreal species (also collected and later named "Dendrobates fuguritus" by our colleague Philip Silverstone). Other dendrobatids found nearby included Phyllobates aurotaenia (Boulenger, 1913), which was then being used for poisoning blowgun darts, and also the nontoxic species that we name Silverstoneia dalyi herein. (Photograph by C. W. Myers, 2 km above Playa de Oro, Chocó, February 16, 1971.) in Review of the Frog Genus Silverstoneia, with Descriptions of Five New Species from the Colombian Chocó (Dendrobatidae: Colostethinae)
FIG, 1. John William Daly (1933–2008) on the upper Río San Juan. This paper is dedicated to John Daly, our late friend and colleague, who helped collect three of the new species here described. In addition to his globally acclaimed discoveries in chemistry and pharmacology, John was an accomplished field herpetologist who contributed importantly to the systematics and natural history of dendrobatoid frogs (see Grant et al., 2006; Myers, 2009). This photograph shows John at age 37, with the upper Río San Juan behind him and branches overhead of a madroño tree (probably Garcinia magnifolia, syn. Rheedia chocoensis, Clusiaceae). When in South America, John was never far from a dendrobatid frog—this time, in the tree above his head, a tiny, undescribed semiarboreal species (also collected and later named "Dendrobates fuguritus" by our colleague Philip Silverstone). Other dendrobatids found nearby included Phyllobates aurotaenia (Boulenger, 1913), which was then being used for poisoning blowgun darts, and also the nontoxic species that we name Silverstoneia dalyi herein. (Photograph by C. W. Myers, 2 km above Playa de Oro, Chocó, February 16, 1971.)
Molecular Determinants and Pharmacological Analysis for a Class of Competitive Non-transported Bicyclic Inhibitors of the Betaine/GABA Transporter BGT1: Modeling Data
<p>This archive contains the modeling data for the study <a href="https://www.frontiersin.org/articles/10.3389/fchem.2021.736457/full">"Molecular Determinants and Pharmacological Analysis for a Class of Competitive Non-transported Bicyclic Inhibitors of the Betaine/GABA Transporter BGT1"</a> (doi: 10.3389/fchem.2021.736457).</p> <p>The following data sets are available:</p> <ul> <li>Induced fit docking results of all mentioned compounds in the study: <br> ifd_hBGT1_occ_clustering_all_compounds.zip<br> </li> <li>MD simulations of bicyclo-GABA and compound 1 (100ns, 3 replica):<br> MD_simulation_bicyclo-GABA_run1.zip<br> MD_simulation_bicyclo-GABA_run2.zip<br> MD_simulation_bicyclo-GABA_run3.zip<br> MD_simulation_cmd1_run1.zip<br> MD_simulation_cmd1_run2.zip<br> MD_simulation_cmd1_run3.zip</li> </ul> <p>A detailed description of the methods is available in the aforementioned publication.</p> <p> </p> <p>The compound numbering in the uploaded files differs from the compound numbering in the mentioned study:</p> <p> </p> <p>study / upload</p> <p>bicyclo-GABA / cmd4</p> <p>1 / IIa</p> <p>2 /8-2</p> <p>3 / 8-3</p> <p>4a / 7-1</p> <p>4b / 7-2</p> <p>4c / 7-3</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Diabetes Pharmacology Ontology
<p>The Diabetes Pharmacology Ontology contains the classes needed to describe antihyperglycemic therapies, pharmacotherapy factors, and diagnostic factors.</p>
Effectiveness of Combining Behavioral and Pharmacologic Therapy for Complex Insomnia in Veterans With PTSD
ClinicalTrials.gov study NCT03937713. IPD Sharing: YES. Countries: 1. Publications: 1.
Molecular dynamics dataset for pharmacological repositioning in the treatment of non-small-cell lung cancer
<p><span>Non-small cell lung cancer (NSCLC) is a type of lung cancer associated with translocation of the EML4 and ALK genes on the short arm of chromosome 2. This leads to the development of an aberrant protein kinase with a deregulated catalytic domain, the cdALK<sup>+</sup>. Currently, different ALK inhibitors (iALKs) have been proposed to treat ALK<sup>+ </sup>NSCLC patients.</span> <span>However, the recent resistance to iALKs stimulates the exploration of new iALKs for NSCLC. Here, we describe an <em>in silico</em> approach to finding FDA-approved drugs that can be used by pharmacological repositioning as iALK. We used homology modelling to obtain a structural model of cdALK<sup>+</sup> protein and then performed molecular docking and molecular dynamics of the complex cdALK<sup>+</sup>-iALKs to generate the pharmacophore model. The pharmacophore was used to identify potential iALKs from FDA-approved drugs library by ligand-based virtual screening. Four pharmacophores with different atomistic characteristics were generated, resulting in six drugs that satisfied the proposed atomistic positions</span> <span>and coupled at the ATP-binding site. Mitoxantrone, riboflavin and abacavir exhibit the best interaction energies with 228.29, 165.40 and 133.48 kjoul/mol respectively. In addition, the special literature proposed these drugs for other types of diseases due to pharmacological repositioning. This study proposes FDA-approved drugs with ALK inhibitory characteristics. Moreover, we identified pharmacophores sites that can be tested with other pharmacological libraries</span><span>.</span></p>
Data from: Pharmacological HIF-1 activation upregulates extracellular vesicle production synergistically with adiponectin through transcriptional induction and protein stabilization of T-cadherin
<p>Pharmacological activation of hypoxia-inducible factor 1alpha (HIF-1α), a hypoxia-responsive transcription factor, has attracted increasing attention due to its efficacy not only in renal anemia but also in various disease models. Our study demonstrated that a HIF-1 activator enhanced exosome production from cultured endothelial cells synergistically with adiponectin, an adipocyte-derived factor, through both transcriptional induction and posttranscriptional stabilization of an adiponectin binding partner, T-cadherin. Increased exosome levels were observed in wild-type mice but not in T-cadherin null mice after consecutive administration of roxadustat. Adiponectin- and T-cadherin-dependent increased exosome production may be involved in the pleiotropic effects of HIF-1 activators.</p>
Influenza A virus liquid condensates can undergo pharmacological hardening
<p>Data generated and codes used for the publication titled "Influenza A virus liquid condensates can undergo pharmacological hardening"</p>
Supporting material for "Pharmacological validation of individual animal locomotion, temperature and behavioural analysis in group-housed rats using a novel automated home cage analysis system: a comparison with the modified Irwin test"
<p>The data were uploaded to support the manuscript "Pharmacological validation of individual animal locomotion, temperature and behavioural analysis in group-housed rats using a novel automated home cage analysis system: a comparison with the modified Irwin test" for the submission to Journal of Pharmacological and Toxicological Methods.</p>
Meta-analytic dataset for the network meta-analysis on pharmacological and dietary-supplement treatments for autism (PMID: 35246237)
<p>The meta-analytic dataset consists of the underlying data for the network meta-analysis on pharmacological and dietary-supplement treatments for autism (PMID: 35246237): Siafis, S., Çıray, O., Wu, H., et al. Pharmacological and dietary-supplement treatments for autism spectrum disorder: a systematic review and network meta-analysis. Molecular Autism, 13, 10 (2022). <a href="https://doi.org/10.1186/s13229-022-00488-4" target="_new" rel="noreferrer">https://doi.org/10.1186/s13229-022-00488-4</a></p> <p>This dataset was published as Additional File 7 in the aforementioned article, which is licensed under a Creative Commons Attribution 4.0 International License (<a href="https://creativecommons.org/licenses/by/4.0/" target="_new" rel="noreferrer">https://creativecommons.org/licenses/by/4.0/</a>).</p>
Efficacy and in vitro pharmacological assessment of novel N-hydroxypyridinediones as hepatitis B virus ribonuclease H inhibitors
<p>The data here is summarized in Efficacy and in vitro pharmacological assessment of novel N-hydroxypyridinediones as hepatitis B virus ribonuclease H inhibitors by Woodson, et al. </p>
Network pharmacology and UPLC-Q-TOF-MS-based method to explore the underlying mechanism of Shaoyao–Gancao decoction acting on atopic dermatitis
<p>This study aimed to investigate the immunomodulation and anti-inflammatory effects of SGD and further explore its pharmacodynamics material basis and potential molecular mechanisms on atopic dermatitis (AD) disorder.</p>
A novel preclinical secondary pharmacology resource illuminates target-adverse drug reaction associations of marketed drugs - Supplementary Material
<p>All Supplementary materials and source data for the manuscript.</p> <p>The reported analyses and results can be reproduced via the described IPython notebooks which can be found under www.github.com/Novartis/SPD</p>
Pharmacological induction of translational readthrough of nonsense mutations in the retinoblastoma (RB1) gene
<p>Original blot images and qRT-PCR data.</p>
Exploring the anti-glioma mechanism of the active components of Cortex Periplocae based on network pharmacology and iTRAQ proteomics in vitro
<p>Hierarchical clustering analysis of candidate proteins was illustrated in heat map, which showed obvious differences between CP-induced cells and controls (Fig. 6). Each column is a sample and each rowindicates a differentially expressed protein. Log values (log<sub>2</sub>expression) of significantly differentially expressed proteins in different samples are displayed in heat maps in different colors. GreenandRedrepresent up-regulation and down-regulation, respectively. The gray part represents no quantitative information of the proteins. T1, T2 and T3 means the CP-treated U251 cells group and C2, C2 and C3 means control group (n=3).</p>
Clinical Pharmacology of Electronic Cigarettes
ClinicalTrials.gov study NCT02470754. IPD Sharing: NO. Countries: 1. Publications: 1.
Behavioral and Pharmacologic Treatment of Binge Eating and Obesity: Acute Treatment
ClinicalTrials.gov study NCT03045341. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Pharmacological Ascorbate for Lung Cancer
ClinicalTrials.gov study NCT02420314. IPD Sharing: YES. Countries: 1. Publications: 2.
ScienceDex guides
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