cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2c3j56
title: CCDC 2178127: Experimental Crystal Structure Determination

description: Related Article: Svetlana E. Nikiforova, Alexey S. Kubasov, Lyudmila V. Goeva, Varvara V. Avdeeva, Elena A. Malinina, Nikolay T. Kuznetsov|2022|Polyhedron|226|116108|doi:10.1016/j.poly.2022.116108
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.7060305
title: A systematic assessment of deep learning methods for drug response prediction: from in-vitro to clinical application

description: https://github.com/LihongLab/Suppl-data-Benchmark ## GDSC dataset **Table S3.** GDSC gene expression profiles for 966 cancer cell lines, where each column represents a cell line in the form of its name and tissue collection site, and each row represents a gene in the form of the HGNC symbol. **Table S4.** GDSC gene mutation profiles for 966 cancer cell lines, where each column represents a cell line in the form of its name and tissue collection site, and each row represents a gene in the form of the HGNC symbol. The wild type is coded as 1 and the wild type as 0. **Table S5.** GDSC copy number variation profiles for 966 cancer cell lines, where each column represents a cell line in the form of its name and tissue collection site, and each row represents a gene in the form of the HGNC symbol. The copy-neutral is coded as 0 and the deletion or amplification as 1. **Table S6.** GDSC drug response data for 966 cancer cell lines and 282 drugs in the form of the natural logarithm of the IC50 readout. The first column shows the cell line name and tissue collection site, the second column shows the drug name, and the third column shows the drug response readout. **Table S7.** GDSC annotations for 282 drugs include drug name, PubChem CID, PubChem canonical SMILES, Rdkit canonical SMILES, Target Pathway, standard deviation, bimodality coefficient and density coverage. ## TCGA dataset **Table S8.** TCGA gene expression profiles, where each column represents a patient in the form of TCGA patient ID, and each row represents a gene in the form of the HGNC symbol. **Table S9.** TCGA gene mutation profiles, where each column represents a patient in the form of TCGA patient ID, and each row represents a gene in the form of the HGNC symbol. The wild type is coded as 1 and the wild type as 0. **Table S10.** TCGA copy number variation profiles, where each column represents a patient in the form of TCGA patient ID, and each row represents a gene in the form of the HGNC symbol. The copy-neutral is coded as 0 and the deletion or amplification as 1. **Table S11.** TCGA clinical response data. The first column shows the TCGA patient ID, the second column shows the drug name, the third column shows the clinical response category, the fourth column shows the cancer type, and the last column shows the clinical label as responder or non-responder.
DOI: 10.5281/zenodo.7060304
title: A systematic assessment of deep learning methods for drug response prediction: from in-vitro to clinical application

description: https://github.com/LihongLab/Suppl-data-Benchmark ## GDSC dataset **Table S3.** GDSC gene expression profiles for 966 cancer cell lines, where each column represents a cell line in the form of its name and tissue collection site, and each row represents a gene in the form of the HGNC symbol. **Table S4.** GDSC gene mutation profiles for 966 cancer cell lines, where each column represents a cell line in the form of its name and tissue collection site, and each row represents a gene in the form of the HGNC symbol. The wild type is coded as 1 and the wild type as 0. **Table S5.** GDSC copy number variation profiles for 966 cancer cell lines, where each column represents a cell line in the form of its name and tissue collection site, and each row represents a gene in the form of the HGNC symbol. The copy-neutral is coded as 0 and the deletion or amplification as 1. **Table S6.** GDSC drug response data for 966 cancer cell lines and 282 drugs in the form of the natural logarithm of the IC50 readout. The first column shows the cell line name and tissue collection site, the second column shows the drug name, and the third column shows the drug response readout. **Table S7.** GDSC annotations for 282 drugs include drug name, PubChem CID, PubChem canonical SMILES, Rdkit canonical SMILES, Target Pathway, standard deviation, bimodality coefficient and density coverage. ## TCGA dataset **Table S8.** TCGA gene expression profiles, where each column represents a patient in the form of TCGA patient ID, and each row represents a gene in the form of the HGNC symbol. **Table S9.** TCGA gene mutation profiles, where each column represents a patient in the form of TCGA patient ID, and each row represents a gene in the form of the HGNC symbol. The wild type is coded as 1 and the wild type as 0. **Table S10.** TCGA copy number variation profiles, where each column represents a patient in the form of TCGA patient ID, and each row represents a gene in the form of the HGNC symbol. The copy-neutral is coded as 0 and the deletion or amplification as 1. **Table S11.** TCGA clinical response data. The first column shows the TCGA patient ID, the second column shows the drug name, the third column shows the clinical response category, the fourth column shows the cancer type, and the last column shows the clinical label as responder or non-responder.
DOI: 10.5281/zenodo.7041554
title: Dataset of blowfly (Diptera: Calliphoridae) specimens observed along an elevational gradient on Mr. Etna, Sicily.

description: This dataset contains count data for blowflies (Diptera: Calliphoridae) collected at four different elevations along an altitudinal gradient around Mt. Etna, in Sicily (Italy). Samples were collected to determine changes in blowfly community assembly as elevation changes. BlowflyAltitudeSicily_Data.csv is a file that contains the raw count data for species separated by both elevation and sex of the identified specimens. BlowflyAltitudeSicily_Methods.docx is a summarized version of the sampling method relevant to interpreting the data. BlowflyAltitudeSicily_Descriptive.txt is a file describing the column headers in "BlowflyAltitudeSicily_Data.csv".
DOI: 10.5281/zenodo.7060325
title: Dataset of blow fly (Diptera: Calliphoridae) species observed along an elevational gradient on Mt. Etna, Sicily.

description: This dataset contains count data for blow flies (Diptera: Calliphoridae) collected at four different elevations along an altitudinal gradient around Mt. Etna, in Sicily (Italy). Samples were collected to determine changes in blow fly community assembly as elevation changes. BlowflyAltitudeSicily_Data.csv is a file that contains the raw count data for species separated by both elevation and sex of the identified specimens. BlowflyAltitudeSicily_Methods.docx is a summarized version of the sampling method relevant to interpreting the data. BlowflyAltitudeSicily_Descriptive.txt is a file describing the column headers in "BlowflyAltitudeSicily_Data.csv".
DOI: 10.5281/zenodo.7041553
title: Dataset of blow fly (Diptera: Calliphoridae) species observed along an elevational gradient on Mt. Etna, Sicily.

description: This dataset contains count data for blow flies (Diptera: Calliphoridae) collected at four different elevations along an altitudinal gradient around Mt. Etna, in Sicily (Italy). Samples were collected to determine changes in blow fly community assembly as elevation changes. BlowflyAltitudeSicily_Data.csv is a file that contains the raw count data for species separated by both elevation and sex of the identified specimens. BlowflyAltitudeSicily_Methods.docx is a summarized version of the sampling method relevant to interpreting the data. BlowflyAltitudeSicily_Descriptive.txt is a file describing the column headers in "BlowflyAltitudeSicily_Data.csv".
DOI: 10.6084/m9.figshare.20650256
title: Seven Unrecorded Indigenous Fungi from Mudeungsan National Park in Korea

description: Fungi act as important decomposers in the forest environment. They recycle essential nutrients, promote plant growth through mycorrhizal relationships, and act as food for small animals. Samples of 265 indigenous fungal species were collected from Mudeungsan National Park in 2020. These species were identified based on morphological, molecular, and phylogenetic analyses using the internal transcribed spacer (ITS), nuclear large subunit rRNA (LSU), and RNA polymerase II second largest subunit (rpb2) regions. Subsequently, seven species were identified as unrecorded species in Korea: <i>Cordyceps cicadae</i>, <i>Dentocorticium bicolor</i>, <i>Hymenochaete nanospora</i>, <i>Physisporinus crataegi</i>, <i>Rigidoporus piceicola</i>, <i>Russula raoultii</i>, and <i>Scutellinia crinita</i>. This study reveals their detailed macro- and microscopic morphological characteristics with phylogenetic trees to report them as unrecorded species in Korea.
DOI: 10.6084/m9.figshare.20650256.v1
title: Seven Unrecorded Indigenous Fungi from Mudeungsan National Park in Korea

description: Fungi act as important decomposers in the forest environment. They recycle essential nutrients, promote plant growth through mycorrhizal relationships, and act as food for small animals. Samples of 265 indigenous fungal species were collected from Mudeungsan National Park in 2020. These species were identified based on morphological, molecular, and phylogenetic analyses using the internal transcribed spacer (ITS), nuclear large subunit rRNA (LSU), and RNA polymerase II second largest subunit (rpb2) regions. Subsequently, seven species were identified as unrecorded species in Korea: <i>Cordyceps cicadae</i>, <i>Dentocorticium bicolor</i>, <i>Hymenochaete nanospora</i>, <i>Physisporinus crataegi</i>, <i>Rigidoporus piceicola</i>, <i>Russula raoultii</i>, and <i>Scutellinia crinita</i>. This study reveals their detailed macro- and microscopic morphological characteristics with phylogenetic trees to report them as unrecorded species in Korea.
DOI: 10.6084/m9.figshare.20939606
title: Re-Identification on Korean <i>Penicillium</i> Sequences in GenBank Collected by Software GenMine

description: <i>Penicillium</i> species have been actively studied in various fields, and many new and unrecorded species continue to be reported in Korea. Moreover, unidentified and misidentified Korean <i>Penicillium</i> species still exist in GenBank. Therefore, it is necessary to revise the Korean <i>Penicillium</i> inventory based on accurate identification. We collected Korean <i>Penicillium</i> nucleotide sequence records from GenBank using the newly developed software, GenMine, and re-identified Korean <i>Penicillium</i> based on the maximum likelihood trees. A total of 1681 Korean <i>Penicillium</i> GenBank nucleotide sequence records were collected from GenBank. In these records, 1208 strains with four major genes (Internal Transcribed Spacer rDNA region, β-tubulin, Calmodulin and RNA polymerase II) were selected for <i>Penicillium</i> re-identification. Among 1208 strains, 927 were identified, 82 were identified as other genera, the rest remained undetermined due to low phylogenetic resolution. Identified strains consisted of 206 <i>Penicillium</i> species, including 156 recorded species and 50 new species candidates. However, 37 species recorded in the national list of species in Korea were not found in GenBank. Further studies on the presence or absence of these species are required through literature investigation, additional sampling, and sequencing. Our study can be the basis for updating the Korean <i>Penicillium</i> inventory.
DOI: 10.6084/m9.figshare.20939606.v1
title: Re-Identification on Korean <i>Penicillium</i> Sequences in GenBank Collected by Software GenMine

description: <i>Penicillium</i> species have been actively studied in various fields, and many new and unrecorded species continue to be reported in Korea. Moreover, unidentified and misidentified Korean <i>Penicillium</i> species still exist in GenBank. Therefore, it is necessary to revise the Korean <i>Penicillium</i> inventory based on accurate identification. We collected Korean <i>Penicillium</i> nucleotide sequence records from GenBank using the newly developed software, GenMine, and re-identified Korean <i>Penicillium</i> based on the maximum likelihood trees. A total of 1681 Korean <i>Penicillium</i> GenBank nucleotide sequence records were collected from GenBank. In these records, 1208 strains with four major genes (Internal Transcribed Spacer rDNA region, β-tubulin, Calmodulin and RNA polymerase II) were selected for <i>Penicillium</i> re-identification. Among 1208 strains, 927 were identified, 82 were identified as other genera, the rest remained undetermined due to low phylogenetic resolution. Identified strains consisted of 206 <i>Penicillium</i> species, including 156 recorded species and 50 new species candidates. However, 37 species recorded in the national list of species in Korea were not found in GenBank. Further studies on the presence or absence of these species are required through literature investigation, additional sampling, and sequencing. Our study can be the basis for updating the Korean <i>Penicillium</i> inventory.
DOI: 10.6084/m9.figshare.20457390
title: Fourteen Unrecorded Species of Agaricales Underw. (Agaricomycetes, Basidiomycota) from the Republic of Korea

description: Agaricales species form pileate-stipitate fruiting bodies and play important roles in maintaining the terrestrial ecosystem as decomposers, symbionts, and pathogens. Approximately 23,000 Agaricales species have been known worldwide, and 937 species have been recorded in the Republic of Korea. However, most of them were identified solely based on morphological characteristics that often led to misidentifications. The specimens collected from 2018 to 2020 in the Republic of Korea were identified based on phylogenetic analysis of the internal transcribed spacer (ITS) sequences. Their identities were confirmed by microscopic characteristics. As a result, 14 Agaricales species were discovered for the first time in the Republic of Korea. They belonged to nine genera: <i>Agaricus</i>, <i>Calocybe</i>, <i>Cortinarius</i>, <i>Hygrocybe</i>, <i>Inocybe</i>, <i>Lepista</i>, <i>Leucoagaricus</i>, <i>Marasmius</i>, and <i>Psathyrella</i>. Detailed macroscopic and microscopic descriptions were provided to help distinguish these species. The morphological and molecular data provided in this study will serve as reliable references for the identification of Agaricales species.
DOI: 10.6084/m9.figshare.19662886.v1
title: Genetic screening of <i>TGFBI</i> in Iranian patients with <i>TGFBI</i>-associated corneal dystrophies and a meta-analysis of global variation frequencies

description: Transforming growth factor beta-induced (<i>TGFBI</i>)-associated corneal dystrophies (CDs) are a clinically heterogeneous group of CDs caused by mutations in the <i>TGFBI</i> gene. Nucleotide sequences encoding two arginine residues at positions 124 and 555 in TGFBI protein are mutation hotspots. We screened regions of <i>TGFBI</i> that include the hotspots in a cohort of Iranian patients with <i>TGFBI</i>-associated CDs. We also performed a meta-analysis for frequencies of all reported <i>TGFBI</i> mutations. Twenty-four <i>TGFBI</i>-associated CD-diagnosed patients were recruited. Exons 4 and 12 of <i>TGFBI</i> were amplified by the polymerase chain reaction and sequenced by Sanger protocol. A meta-analysis on reported <i>TGFBI</i> sequence data was done by reviewing all published relevant articles available in NCBI. Twenty-two out of 24 patients had mutations in exons 4 or 12 of <i>TGFBI</i>. The most frequent mutations were p.Arg124Cys, p.Arg124His, and p.Arg555Trp; each of these was found in six families. Three other missense mutations including p.Arg555Gln, p.Ile522Asn, and p.Ala546Thr were also identified. The data suggested a fairly tight genotype/phenotype correlation for the most common CDs. Literature review evidenced that the reported mutations affected less than 30% of the amino acids of the TGFBI protein and that p.Arg124His, p.Arg124Cys, p.Arg555Trp, p.Arg124Leu, p.Arg555Gln, and p.His626Arg were the most frequent mutations. <i>TGFBI</i> mutation profile of Iranian patients is very similar to that of the rest of the world. The meta-analysis confirmed the worldwide prevalence of p.Arg124 and p.Arg555, showed that p.His626Arg is also relatively frequent, and evidenced the value of screening exons 4 and 12 of <i>TGFBI</i>.
DOI: 10.6084/m9.figshare.19662886
title: Genetic screening of <i>TGFBI</i> in Iranian patients with <i>TGFBI</i>-associated corneal dystrophies and a meta-analysis of global variation frequencies

description: Transforming growth factor beta-induced (<i>TGFBI</i>)-associated corneal dystrophies (CDs) are a clinically heterogeneous group of CDs caused by mutations in the <i>TGFBI</i> gene. Nucleotide sequences encoding two arginine residues at positions 124 and 555 in TGFBI protein are mutation hotspots. We screened regions of <i>TGFBI</i> that include the hotspots in a cohort of Iranian patients with <i>TGFBI</i>-associated CDs. We also performed a meta-analysis for frequencies of all reported <i>TGFBI</i> mutations. Twenty-four <i>TGFBI</i>-associated CD-diagnosed patients were recruited. Exons 4 and 12 of <i>TGFBI</i> were amplified by the polymerase chain reaction and sequenced by Sanger protocol. A meta-analysis on reported <i>TGFBI</i> sequence data was done by reviewing all published relevant articles available in NCBI. Twenty-two out of 24 patients had mutations in exons 4 or 12 of <i>TGFBI</i>. The most frequent mutations were p.Arg124Cys, p.Arg124His, and p.Arg555Trp; each of these was found in six families. Three other missense mutations including p.Arg555Gln, p.Ile522Asn, and p.Ala546Thr were also identified. The data suggested a fairly tight genotype/phenotype correlation for the most common CDs. Literature review evidenced that the reported mutations affected less than 30% of the amino acids of the TGFBI protein and that p.Arg124His, p.Arg124Cys, p.Arg555Trp, p.Arg124Leu, p.Arg555Gln, and p.His626Arg were the most frequent mutations. <i>TGFBI</i> mutation profile of Iranian patients is very similar to that of the rest of the world. The meta-analysis confirmed the worldwide prevalence of p.Arg124 and p.Arg555, showed that p.His626Arg is also relatively frequent, and evidenced the value of screening exons 4 and 12 of <i>TGFBI</i>.
DOI: 10.6084/m9.figshare.19372811
title: Adherence and satisfaction in Argus II prosthesis users: a self determination theory model

description: Self-determination theory (SDT) of human motivation was used to examine associations between different forms of motivation in Argus II retinal prosthesis users and their engagement and satisfaction with the Argus device. Nine subjects were administered: 1) a Situational Motivation Scale (SIMS) questionnaire to measure intrinsic motivation, identified regulation, external regulation, and amotivation, and 2) the Argus questionnaire (AQ) which was organized into 5 categories to measure ‘Decision to get an Argus implant,’ ’Self-perception as an Argus user’, ‘Utility of Argus,’ ‘Perceived competence,’ and ‘Family support.’ Spearman correlations (<i>r<sub>s</sub></i>) were used to find associations between measures from SIMS and AQ. Nine subjects completed both questionnaires. Statistically significant associations were observed between identified regulation and AQ items from categories: Decision to get Argus, Self-perception, Utility of Argus, and Perceived competence; and between intrinsic motivation and AQ items from Self-perception and Utility. External regulation was negatively associated with Family support, and amotivation was associated with one item from Self-perception. Engagement with the device and satisfaction were associated to both identified regulation and intrinsic motivation. There was no significant relationship between external regulation and adherence to the device. The SDT model can be used to investigate the types of motivation that influence uptake and engagement of the Argus device. Clinicians can use this knowledge to improve outcomes by supporting confidence in users and by encouraging them to maintain internalization and continued commitment to adherence.
DOI: 10.6084/m9.figshare.19372811.v1
title: Adherence and satisfaction in Argus II prosthesis users: a self determination theory model

description: Self-determination theory (SDT) of human motivation was used to examine associations between different forms of motivation in Argus II retinal prosthesis users and their engagement and satisfaction with the Argus device. Nine subjects were administered: 1) a Situational Motivation Scale (SIMS) questionnaire to measure intrinsic motivation, identified regulation, external regulation, and amotivation, and 2) the Argus questionnaire (AQ) which was organized into 5 categories to measure ‘Decision to get an Argus implant,’ ’Self-perception as an Argus user’, ‘Utility of Argus,’ ‘Perceived competence,’ and ‘Family support.’ Spearman correlations (<i>r<sub>s</sub></i>) were used to find associations between measures from SIMS and AQ. Nine subjects completed both questionnaires. Statistically significant associations were observed between identified regulation and AQ items from categories: Decision to get Argus, Self-perception, Utility of Argus, and Perceived competence; and between intrinsic motivation and AQ items from Self-perception and Utility. External regulation was negatively associated with Family support, and amotivation was associated with one item from Self-perception. Engagement with the device and satisfaction were associated to both identified regulation and intrinsic motivation. There was no significant relationship between external regulation and adherence to the device. The SDT model can be used to investigate the types of motivation that influence uptake and engagement of the Argus device. Clinicians can use this knowledge to improve outcomes by supporting confidence in users and by encouraging them to maintain internalization and continued commitment to adherence.
DOI: 10.5281/zenodo.5336819
title: Visual function and neuropsychological profile in children with Cerebral Visual Impairment

description: This database includes the raw data linked with the paper “Visual function and neuropsychological profile in children with Cerebral Visual Impairment” published on “Children”. In this paper, we aimed to a) describe the clinical and neuropsychological profiles b) to investigate the possible effects of visual functions on neuropsychological performance of a cohort of children diagnosed with CVI. The first sheet of the spreadsheet includes data on medical history, visual functions neuropsychological evaluations of the 51 subjects included in the descriptive study. The second sheet includes data on visual functions and neuropsychological evalutations for correlation analyses. All the data, except for age, are encoded as reported in the third sheet. Fifty-one children with CVI were included in the descriptive study, and 40 children were selected for the correlation analyses. For each participant, we collected data on neuropsychological assessment, basic visual functions, global development features. Results showed that oculomotor dysfunction involving saccades and smooth pursuit may be a core symptom of CVI and might have a significant impact on cognitive visual and other neuropsychological abilities. Furthermore, visual acuity and contrast sensitivity may influence cognitive, cognitive visual and academic performances. Our findings suggest the importance of a comprehensive assessment of both visual and neuropsychological functions in children when CVI is suspected, to provide a more comprehensive functional profile and define the best habilitation strategy to sustain functional vision.
description: Funding: Ricerca Corrente 2020-2021, Ministry of Health (Italy)