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Illinois Data Bank Dataset Search Results
Dataset Search Results
published: 2016-12-19
Hahn, James (2016): API analysis of the Minrva mobile app (May 2015 – December 2015). University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-5495131_V1
Files in this dataset represent an investigation into use of the Library mobile app Minrva during the months of May 2015 through December 2015. During this time interval 45,975 API hits were recorded by the Minrva web server. The dataset included herein is an analysis of the following: 1) a delineation of API hits to mobile app modules use in the Minrva app by month, 2) a general analysis of Minrva app downloads to module use, and 3) the annotated data file providing associations from API hits to specific modules used, organized by month (May 2015 – December 2015).
keywords:
API analysis; log analysis; Minrva Mobile App
published: 2021-07-15
Castro, Daniel; Sweedler, Jonathan (2021): High-Throughput Single-Organelle Dataset. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-5949772_V1
The dataset contains the high-throughput matrix-assisted laser desorption/ionization mass spectrometry XmL files for the atrial gland and red hemiduct of Aplysia californica.
keywords:
Dense-core vesicle; High-throughput; Mass Spectrometry; MALDI; Organelle; Image-Guided; Atrial gland; red hemiduct; Lucent Vesicle
published: 2023-03-28
Hsiao, Tzu-Kun; Torvik, Vetle (2023): OpCitance: Citation contexts identified from the PubMed Central open access articles. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4353270_V2
Sentences and citation contexts identified from the PubMed Central open access articles ---------------------------------------------------------------------- The dataset is delivered as 24 tab-delimited text files. The files contain 720,649,608 sentences, 75,848,689 of which are citation contexts. The dataset is based on a snapshot of articles in the XML version of the PubMed Central open access subset (i.e., the PMCOA subset). The PMCOA subset was collected in May 2019. The dataset is created as described in: Hsiao TK., & Torvik V. I. (manuscript) OpCitance: Citation contexts identified from the PubMed Central open access articles. <b>Files</b>: • A_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with A. • B_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with B. • C_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with C. • D_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with D. • E_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with E. • F_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with F. • G_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with G. • H_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with H. • I_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with I. • J_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with J. • K_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with K. • L_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with L. • M_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with M. • N_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with N. • O_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with O. • P_p1_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with P (part 1). • P_p2_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with P (part 2). • Q_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with Q. • R_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with R. • S_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with S. • T_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with T. • UV_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with U or V. • W_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with W. • XYZ_journal_IntxtCit.tsv – Sentences and citation contexts identified from articles published in journals with journal titles starting with X, Y or Z. Each row in the file is a sentence/citation context and contains the following columns: • pmcid: PMCID of the article • pmid: PMID of the article. If an article does not have a PMID, the value is NONE. • location: The article component (abstract, main text, table, figure, etc.) to which the citation context/sentence belongs. • IMRaD: The type of IMRaD section associated with the citation context/sentence. I, M, R, and D represent introduction/background, method, results, and conclusion/discussion, respectively; NoIMRaD indicates that the section type is not identifiable. • sentence_id: The ID of the citation context/sentence in the article component • total_sentences: The number of sentences in the article component. • intxt_id: The ID of the citation. • intxt_pmid: PMID of the citation (as tagged in the XML file). If a citation does not have a PMID tagged in the XML file, the value is "-". • intxt_pmid_source: The sources where the intxt_pmid can be identified. Xml represents that the PMID is only identified from the XML file; xml,pmc represents that the PMID is not only from the XML file, but also in the citation data collected from the NCBI Entrez Programming Utilities. If a citation does not have an intxt_pmid, the value is "-". • intxt_mark: The citation marker associated with the inline citation. • best_id: The best source link ID (e.g., PMID) of the citation. • best_source: The sources that confirm the best ID. • best_id_diff: The comparison result between the best_id column and the intxt_pmid column. • citation: A citation context. If no citation is found in a sentence, the value is the sentence. • progression: Text progression of the citation context/sentence. <b>Supplementary Files</b> • PMC-OA-patci.tsv.gz – This file contains the best source link IDs for the references (e.g., PMID). Patci [1] was used to identify the best source link IDs. The best source link IDs are mapped to the citation contexts and displayed in the *_journal IntxtCit.tsv files as the best_id column. Each row in the PMC-OA-patci.tsv.gz file is a citation (i.e., a reference extracted from the XML file) and contains the following columns: • pmcid: PMCID of the citing article. • pos: The citation's position in the reference list. • fromPMID: PMID of the citing article. • toPMID: Source link ID (e.g., PMID) of the citation. This ID is identified by Patci. • SRC: The sources that confirm the toPMID. • MatchDB: The origin bibliographic database of the toPMID. • Probability: The match probability of the toPMID. • toPMID2: PMID of the citation (as tagged in the XML file). • SRC2: The sources that confirm the toPMID2. • intxt_id: The ID of the citation. • journal: The first letter of the journal title. This maps to the *_journal_IntxtCit.tsv files. • same_ref_string: Whether the citation string appears in the reference list more than once. • DIFF: The comparison result between the toPMID column and the toPMID2 column. • bestID: The best source link ID (e.g., PMID) of the citation. • bestSRC: The sources that confirm the best ID. • Match: Matching result produced by Patci. [1] Agarwal, S., Lincoln, M., Cai, H., & Torvik, V. (2014). Patci – a tool for identifying scientific articles cited by patents. GSLIS Research Showcase 2014. http://hdl.handle.net/2142/54885 • intxt_cit_license_fromPMC.tsv – This file contains the CC licensing information for each article. The licensing information is from PMC's file lists [2], retrieved on June 19, 2020, and March 9, 2023. It should be noted that the license information for 189,855 PMCIDs is <b>NO-CC CODE</b> in the file lists, and 521 PMCIDs are absent in the file lists. The absence of CC licensing information does not indicate that the article lacks a CC license. For example, PMCID: 6156294 (<b>NO-CC CODE</b>) and PMCID: 6118074 (absent in the PMC's file lists) are under CC-BY licenses according to their PDF versions of articles. The intxt_cit_license_fromPMC.tsv file has two columns: • pmcid: PMCID of the article. • license: The article’s CC license information provided in PMC’s file lists. The value is nan when an article is not present in the PMC’s file lists. [2] https://www.ncbi.nlm.nih.gov/pmc/tools/ftp/ • Supplementary_File_1.zip – This file contains the code for generating the dataset.
keywords:
citation context; in-text citation; inline citation; bibliometrics; science of science
published: 2023-04-12
Han, Edmund; Nahid, Shahriar Muhammad; Rakib, Tawfiqur; Nolan, Gillian; F. Ferrari, Paolo; Hossain, M. Abir ; Schleife, André ; Nam, SungWoo; Ertekin, Elif; van der Zande, Arend; Huang, Pinshane (2023): Data for Bend-induced ferroelectric domain walls in α-In2Se3. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-1187822_V1
STEM images of kinks in α-In2Se3, DFT calculation of bending of α-In2Se3, PFM on as exfoliated and controllably bend α-In2Se3
published: 2023-08-11
Li, Shuai; Leakey, Andrew D.B.; Moller, Christopher A.; Montes, Christopher M.; Sacks, Erik J.; DeKyoung, Lee; Ainsworth, Elizabeth A. (2023): Similar photosynthetic, but different yield responses of C3 and C4 crops to elevated O3. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9446886_V1
This dataset contains leaf photosynthetic and biochemical traits, plant biomass, and yield in five C3 crops (chickpea, rice, snap bean, soybean, wheat) and four C4 crops (sorghum, maize, Miscanthus × giganteus, switchgrass) grown under ambient and elevated O3 concentration ([O3]) in the field at free-air O3 concentration enrichment (O3-FACE) facilities over the past 20 years.
keywords:
C3 and C4 crops; elevated O3; FACE; photosynthesis; yield
published: 2024-01-30
Aishwarya, Anuva; Madhavan, Vidya (2024): Data for Melting of the charge density wave by generation of pairs of topological defects in UTe2. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6515700_V1
The data files are for the paper entitled: Melting of the charge density wave by generation of pairs of topological defects in UTe2 to be published in Nature Physics. The data was obtained on a 300 mK custom designed Unisoku scanning tunneling microscope using the Nanonis module. All the data files have been named based on the Figure numbers that they represent.
keywords:
superconductivity; triplet; topology; heavy fermion; Kondo; magnetic field; charge density wave
published: 2023-08-02
Jeng, Amos; Bosch, Nigel; Perry, Michelle (2023): Data for: Phatic Expressions Influence Perceived Helpfulness in Online Peer Help-Giving: A Mixed Methods Study. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6591732_V1
This dataset was developed as part of an online survey study that investigates how phatic expressions—comments that are social rather than informative in nature—influence the perceived helpfulness of online peer help-giving replies in an asynchronous college course discussion forum. During the study, undergraduate students (N = 320) rated and described the helpfulness of examples of replies to online requests for help, both with and without four types of phatic expressions: greeting/parting tokens, other-oriented comments, self-oriented comments, and neutral comments.
keywords:
help-giving; phatic expression; discussion forum; online learning; engagement
published: 2023-09-13
Shen, Chengze; Liu, Baqiao; Williams, Kelly P.; Warnow, Tandy (2023): Additional datasets (RNASim10k) for EMMA: A New Method for Computing Multiple Sequence Alignments given a Constraint Subset Alignment. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4194451_V1
This upload contains one additional set of datasets (RNASim10k, ten replicates) used in Experiment 2 of the EMMA paper (appeared in WABI 2023): Shen, Chengze, Baqiao Liu, Kelly P. Williams, and Tandy Warnow. "EMMA: A New Method for Computing Multiple Sequence Alignments given a Constraint Subset Alignment". The zipped file has the following structure: 10k |__R0 |__unaln.fas |__true.fas |__true.tre |__R1 ... # Alignment files: 1. `unaln.fas`: all unaligned sequences. 2. `true.fas`: the reference alignment of all sequences. 3. `true.tre`: the reference tree on all sequences. For other datasets that uniquely appeared in EMMA, please refer to the related dataset (which is linked below): Shen, Chengze; Liu, Baqiao; Williams, Kelly P.; Warnow, Tandy (2022): Datasets for EMMA: A New Method for Computing Multiple Sequence Alignments given a Constraint Subset Alignment. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2567453_V1
keywords:
SALMA;MAFFT;alignment;eHMM;sequence length heterogeneity
published: 2017-09-16
Mirarab, Siavash; Warnow, Tandy (2017): Data for 16S and 23S rRNA alignments. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-1614388_V1
This dataset contains the data for 16S and 23S rRNA alignments including their reference trees. The original alignments are from the Gutell Lab CRW, currently located at https://crw-site.chemistry.gatech.edu/DAT/3C/Alignment/.
published: 2019-07-11
Daniels, Melissa; Larson, Eric (2019): Data for Effects of forest windstorm disturbance on invasive plants in protected areas of southern Illinois, USA. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-1401121_V1
We studied the effect of windstorm disturbance on forest invasive plants in southern Illinois. This data includes raw data on plant abundance at survey points, compiled data used in statistical analyses, and spatial data for surveyed plots and units. This file package also includes a readme.doc file that describes the data in detail, including attribute descriptions.
keywords:
tornado, blowdowns, derecho, invasive plants, Shawnee National Forest, southern Illinois
published: 2022-03-30
Tiemann, Jeremy S.; Stodola, Alison P.; Douglass, Sarah A.; Vinsel, Rachel M.; Cummings, Kevin S. (2022): Dataset associated with Nonindigenous Aquatic Mollusks in Illinois manuscript. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8947838_V1
This dataset is associated with a larger manuscript published in 2022 in the Illinois Natural History Survey Bulletin to summarize all known records for nonindigenous aquatic mollusks in Illinois, and full sources are referenced within the manuscript. We examined museum holdings, literature accounts, publicly available databases sponsored by the U.S. Geological Survey (USGS) - Nonindigenous Aquatic Species program (http://nas.er.usgs.gov/.) and InvertEBase (invertebase.org). We also included sporadic field survey data of encounters of nonindigenous aquatic species from colleagues within the Illinois Natural History Survey, Illinois Department of Natural Resources, U.S. Fish and Wildlife Service, county forest preserve districts, and other natural resource agencies about their encounters with nonindigenous aquatic mollusk species. Lastly, we examined the role and utility of citizen-science data to document occurrences of nonindigenous aquatic mollusk species. We queried iNaturalist (www.inaturalist.org) for all available nonindigenous freshwater mollusk data for Illinois. Table heading descriptions (if not intuitive) are: “INHS verified” is whether an INHS staff member verified the record by observing vouchered specimen or photograph; “Source” is where a record was accessed or obtained; “individualCount” is number collected or observed in a record; “MuseumCode” is standard museum abbreviation or acronym; “Institution” is source that housed or reported a record, and this also includes the spelled-out museum code; “Collectors” typically indicates who collected the specimen or voucher; “Lat_Long determined by” denotes whether collection coordinates were stated by the collector or by a curator (using inference from data available); “fieldNumber” typically indicates a unique field number that a collector may have used in the field; “identifiedBy” typically explains who identified a specimen or verified a specimen identification.
keywords:
Illinois; Exotic species; Non-native aquatic species; NAS; Aquatic Invasive Species; AIS; Mollusk
published: 2009-06-19
Liu, Kevin; Raghavan, Sindhu; Nelesen, Serita; Linder, C. Randall; Warnow, Tandy (2009): Data for Rapid and Accurate Large-Scale Coestimation of Sequence Alignments and Phylogenetic Trees. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-5139418_V1
This dataset contains the data for SATe-I. SATe-I data was used in the following article: K. Liu, S. Raghavan, S. Nelesen, C. R. Linder, T. Warnow, "Rapid and Accurate Large-Scale Coestimation of Sequence Alignments and Phylogenetic Trees," Science, vol. 324, no. 5934, pp. 1561-1564, 19 June 2009.
published: 2023-12-19
Bush, Daniel; Calla, Bernarda; Berenbaum, May (2023): Data for "An Aspergillus Strain from Bee Bread of the Western Honey Bee (Apis mellifera) Displays Adaptations to Distinctive Features of the Hive Environment". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7212497_V1
Data for the Appendices of Bush et al. article published in Ecology and Evolution. Contains genomic analysis information for a strain of Aspergillus flavus isolated from bee bread in East Central Illinois.
keywords:
Excel; UIUC; Evolution and Ecology; Aspergillus flavus; genome
published: 2023-07-31
Zhang, Yue; Hossain, Mohammad Abir; Hwang, Kelly; Ferrari, Paolo; Maduzia, Joe; Pena, Tera; Wu, Stephen; Ertekin, Elif; van der Zande, Arend (2023): Dataset for Design and Pattern Strain in 2D materials. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2595358_V1
published: 2022-05-16
Clem, Scott; Hobson, Keith; Harmon-Threatt, Alexandra (2022): Raw data and code for the paper: Do Nearctic hover flies (Diptera: Syrphidae) engage in long-distance migration? An assessment of evidence and mechanisms. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6560908_V1
This dataset is for the publication "Do Nearctic hover flies (Diptera: Syrphidae) engage in long-distance migration? An assessment of evidence and mechanisms." It consists of 11 Excel spreadsheets and 4 R scripts which correspond to the analyses which were conducted. Paper abstract: Long-distance insect migration is poorly understood despite its tremendous ecological and economic importance. As a group, Nearctic hover flies (Diptera: Syrphidae: Syrphinae), which are crucial pollinators as adults and biological control agents as larvae, are almost entirely unrecognized as migratory despite examples of highly migratory behavior among several Palearctic species. Here, we examined evidence and mechanisms of migration for four hover fly species (Allograpta obliqua, Eupeodes americanus, Syrphus rectus, and Syrphus ribesii) common throughout eastern North America using stable hydrogen isotope (δ2H) measurements of chitinous tissue, morphological assessments, abundance estimations, and cold-tolerance assays. While further studies are needed, non-local isotopic values obtained from hover fly specimens collected in central Illinois support the existence of long-distance fall migratory behavior in Eu. americanus, and to a lesser extent S. ribesii and S. rectus. Elevated abundance of Eu. americanus during the expected autumn migratory period further supports the existence of such behavior. Moreover, high phenotypic plasticity of morphology associated with dispersal coupled with significant differences between local and non-local specimens suggest that Eu. americanus exhibits a unique suite of morphological traits that decrease costs associated with long-distance flight. Finally, compared to the ostensibly non-migratory A. obliqua, Eu. americanus was less cold tolerant, a factor that may be associated with migratory behavior. Collectively, our findings imply that fall migration occurs in Nearctic hover flies, but we consider methodological limitations of our study in addition to potential ecological and economic consequences of these novel findings.
keywords:
Insect migration; hover fly; Syrphidae; stable isotopes; deuterium; morphometrics; cold tolerance
published: 2022-03-01
Cao, Yanghui; Dietrich, Christopher H.; Zahniser, James N.; Dmitriev, Dmitry A. (2022): Dataset for Dense sampling of taxa and characters improves phylogenetic resolution among deltocephaline leafhoppers (Hemiptera: Cicadellidae: Deltocephalinae). University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8842653_V2
The following files were used to reconstruct the phylogeny of the leafhopper subfamily Deltocephalinae, using IQ-TREE v1.6.12 and ASTRAL v 4.10.5. <b>1) taxon_sampling.csv:</b> contains the sequencing ids (1st column) and the taxonomic information (2nd column) of each sample. Sequencing ids were used in the alignment files and partition files. <b>2)concatenated_nt.phy:</b> concatenated nucleotide alignment used for the maximum likelihood analysis of Deltocephalinae by IQ-TREE v1.6.12. The file lists the sequences of 163,365 nucleotide positions from 429 genes in 730 samples. Hyphens are used to represent gaps. <b>3) concatenated_nt_partition.nex:</b> the partitions for the concatenated nucleotide alignment. The file partitions the 163,365 nucleotide characters into 429 character sets, and defines the best substitution model for each character set. <b>4) concatenated_aa.phy:</b> concatenated amino acid alignment used for the maximum likelihood analysis of Deltocephalinae by IQ-TREE v1.6.12. The file gives the sequences of 53,969 amino acids from 429 genes in 730 samples. Hyphens are used to represent gaps. <b>5) concatenated_aa_partition.nex:</b> the partitions for the concatenated amino acid alignment. The file partitions the 53,969 characters into 429 character sets, and defines the best substitution model for each character set. <b>6) concatenated_nt_106taxa.phy:</b> a reduced concatenated nucleotide alignment representing 107 samples x 86 genes. This alignment is used to estimate the divergence times of Deltocephalinae using MCMCTree in PAML v4.9. The file lists the sequences of 79,239 nucleotide positions from 86 genes in 107 samples. Hyphens are used to represent gaps. <b>7) concatenated_nt_106taxa_partition.nex:</b> the partitions for the nucleotide alignment concatenated_nt_106taxa.phy. The file partitions the 79,239 nucleotide characters into 86 character sets, and defines the best substitution model for each character set. <b>8) individual_gene_alignment.zip:</b> contains 429 FAS files, one for each of the partitioned nucleotide character sets in the concatenated_nt_partition.nex file. Hyphens are used to represent gaps. These files were used to construct gene trees using IQ-TREE v1.6.12, followed by multispecies coalescent analysis using ASTRAL v 4.10.5.
published: 2023-12-15
Abidi, Syeda Nayab; Hsu, Felicity; Smith-Bolton, Rachel (2023): Data for Regenerative growth is constrained by brain tumor to ensure proper patterning in Drosophila. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9119268_V1
This page contains the data for the publication "Regenerative growth is constrained by brain tumor to ensure proper patterning in Drosophila" published in PLOS Genetics in 2023.
published: 2023-12-18
Johnson, Claire A.; Benson, Thomas J. (2023): Data from: Dynamic, multi-scale analyses indicate site- and landscape-level forest cover drive Yellow-billed and Black-billed Cuckoo interannual turnover. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2905024_V1
Data in this publication were used to examine the effects of habitat and landscape-level covariates on occupancy and interannual dynamics and the effects of environmental factors on detection of Black-billed Cuckoos and Yellow-billed Cuckoos. Data were collected between 2019-2020 in northern Illinois, USA. Procedures were approved by the Illinois Institutional Animal Care and Use Committee (IACUC), protocol no. 19086.
keywords:
Black-billed Cuckoo; habitat use; multi-scale; occupancy dynamics; turnover; Yellow-billed Cuckoo
published: 2023-01-01
Cao, Yanghui; Dietrich, Christopher H.; Kits, Joel; Dmitriev, Dmitry A.; Xu, Ye; Huang, Min (2023): Datasets for Phylogenomics of microleafhoppers (Hemiptera: Cicadellidae: Typhlocybinae): morphological evolution, divergence times and biogeography. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8636195_V1
The following files were used to reconstruct the phylogeny of the leafhopper subfamily Typhlocybinae, using IQ-TREE v1.6.12 and ASTRAL v 4.10.5. <b>1) Taxon_sampling.csv:</b> contains the sample IDs (1st column) and the taxonomic information (2nd column). Sample IDs were used in the alignment files and partition files. <b>2) concatenated_nt_complete.phy:</b> a complete concatenated nucleotide dataset used for the maximum likelihood analysis by IQ-TREE v1.6.12. The file lists the sequences of 248 samples with 154,992 nucleotide positions (intron included) from 665 loci. Hyphens are used to represent gaps. <b>3) concatenated_nt_complete_partition.nex:</b> the partitioning schemes for concatenated_nt_complete.phy. The file partitions the 154,992 nucleotide characters into 426 character sets, and defines the best substitution model for each character set. <b>4) concatenated_cds_complete.phy:</b> a complete concatenated coding DNA sequence dataset used for the maximum likelihood analysis by IQ-TREE v1.6.12. The file lists the sequences of 248 samples with 153,525 nucleotide positions (intron excluded) from 665 loci. Hyphens are used to represent gaps. <b>5) concatenated_cds_complete_partition.nex:</b> the partitioning schemes for concatenated_cds_complete.phy. The file partitions the 153,525 nucleotide characters into 426 character sets, and defines the best substitution model for each character set. <b>6) concatenated_nt_reduced.phy:</b> a reduced concatenated nucleotide dataset used for the maximum likelihood analysis by IQ-TREE v1.6.12. The file lists the sequences of 248 samples with 95,076 nucleotide positions (intron included) from 374 loci. Hyphens are used to represent gaps. <b>7) concatenated_nt_reduced_partition.nex:</b> the partitioning schemes for concatenated_nt_reduced.phy. The file partitions the 95,076 nucleotide characters into 312 character sets, and defines the best substitution model for each character set. <b>8) concatenated_aa_complete.phy:</b> a complete concatenated amino acid dataset used for the maximum likelihood analysis by IQ-TREE v1.6.12, corresponding to concatenated_cds_complete.phy. The file lists the sequences of 248 samples with 51,175 amino acid positions from 665 loci. Hyphens are used to represent gaps. <b>9) concatenated_aa_complete_partition.nex:</b> the partitioning schemes for concatenated_aa_complete.phy. The file partitions the 51,175 amino acid characters into 426 character sets, and defines the best substitution model for each character set. <b>10) concatenated_aa_reduced.phy:</b> a reduced concatenated amino acid dataset used for the maximum likelihood analysis by IQ-TREE v1.6.12, corresponding to concatenated_nt_reduced.phy. The file lists the sequences of 248 samples with 31,384 amino acid positions from 374 loci. Hyphens are used to represent gaps. <b>11) concatenated_aa_reduced_partition.nex:</b> the partitioning schemes for concatenated_aa_reduced.phy. The file partitions the 31,384 amino acid characters into 312 character sets, and defines the best substitution model for each character set. <b>12) Individual_gene_alignment.zip:</b> contains 426 FASTA files, each one is an alignment for a gene. Hyphens are used to represent gaps. These files were used to construct gene trees using IQ-TREE v1.6.12, followed by multispecies coalescent analysis using ASTRAL v 4.10.5 based the consensus trees with a minimum average bootstrap value of 70.
keywords:
Auchenorrhyncha, Cicadomorpha, Membracoidea, anchored hybrid enrichment
published: 2023-07-28
Njuguna, Joyce; Clark, Lindsay; Lipka , Alexander; Anzoua, Kossonou; Bagmet, Larisa; Chebukin, Pavel; Dwiyanti, Maria; Dzyubenko, Elena; Dzyubenko, Nicolay; Ghimire, Bimal; Jin, Xiaoli; Johnson, Douglas; Nagano, Hironori; Peng, Junhua; Petersen, Karen; Sabitov, Andrey; Seong, Eun; Yamada, Toshihiko; Yoo, Ji; Yu, Chang; Zhao, Hu; Long, Stephen; Sacks, Erik (2023): Data for Genome-wide association and genomic prediction for yield and component traits of Miscanthus sacchariflorus. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6439486_V1
The dataset is for a study conducted to understand genome-wide association (GWA) and genomic prediction of biomass yield and 14 yield-components traits in Miscanthus sacchariflorus. We evaluated a diversity panel with 590 accessions of M. sacchariflorus grown across four years in one subtropical and three temperate locations and genotyped with 268,109 single nucleotide polymorphisms (SNPs).
keywords:
Miscanthus sacchariflorus; genome-wide association analysis; genomic prediction; bioenergy; biomass
published: 2023-01-16
Xie, Yuxuan Richard; Chari, Varsha.K; Castro, Daniel.C; Grant, Romans; Rubakhin , Stanislav S. ; Sweedler, Jonathan V. (2023): Data-Driven and Machine Learning Based Framework for Image-Guided Single-Cell Mass Spectrometry. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7302959_V1
Data sets to reproduce the results provided by the tutorial in paper "Data-Driven and Machine Learning Based Framework for Image-Guided Single-Cell Mass Spectrometry"
published: 2023-04-06
Yao, Lehan; Lyu, Zhiheng; Li, Jiahui; Chen, Qian (2023): Data for Unsupervised Sinogram Inpainting for Nanoparticle Electron Tomography (UsiNet) for missing wedge correction. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7963044_V1
Example data for https://github.com/chenlabUIUC/UsiNet The data contains computer simulated and experimental tilting series (or sinograms) of gold nanoparticles. Two training data examples are provided: 1. simulated_data.zip 2. experimental_data.zip In each zip folder, we include an image_data.zip and a training_data.zip. The former is for viewing and only the latter is needed for model training. For more details, please refer to our GitHub repository.
keywords:
electron tomography; deep learning
published: 2023-06-01
Trapp, Robert (2023): tornado-PGW. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4479773_V1
published: 2023-07-26
Kantola, Ilsa B; Blanc-Betes, Elena; Masters, Michael; Chang, Elliot; Marklein, Alison; Moore, Caitlin; von Haden, Adam; Bernacchi, Carl; Wolf, Adam; Epihov, Dimitar; Beerling, David; DeLucia, Evan (2023): Data for Improved Net Carbon Budgets in the US Midwest through Direct Measured Impacts of Enhanced Weathering. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-1917166_V1
This data set contains data used for “Improved Net Carbon Budgets in the US Midwest through Direct Measured Impacts of Enhanced Weathering.” Data include biomass, soil bulk densities, soil respiration measurements, soil lanthanide element analysis, plant tissue analysis for major cations, and eddy covariance fluxes.
keywords:
agriculture; bioenergy crop; carbon budget; eddy covariance; net ecosystem carbon balance; net primary production; soil respiration; enhanced weathering; carbon dioxide removal; Illinois
published: 2023-07-14
Schneider, Jodi; Das, Susmita; Léveillé, Jacqueline ; Proescholdt, Randi (2023): Data for Post-retraction citation: A review of scholarly research on the spread of retracted science. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3254797_V1
Data for Post-retraction citation: A review of scholarly research on the spread of retracted science Schneider, Jodi; Das, Susmita; Léveillé, Jacqueline; Proescholdt, Randi Contact: Jodi Schneider jodi@illinois.edu & jschneider@pobox.com ********** OVERVIEW ********** This dataset provides further analysis for an ongoing literature review about post-retraction citation. This ongoing work extends a poster presented as: Jodi Schneider, Jacqueline Léveillé, Randi Proescholdt, Susmita Das, and The RISRS Team. Characterization of Publications on Post-Retraction Citation of Retracted Articles. Presented at the Ninth International Congress on Peer Review and Scientific Publication, September 8-10, 2022 hybrid in Chicago. https://hdl.handle.net/2142/114477 (now also in https://peerreviewcongress.org/abstract/characterization-of-publications-on-post-retraction-citation-of-retracted-articles/ ) Items as of the poster version are listed in the bibliography 92-PRC-items.pdf. Note that following the poster, we made several changes to the dataset (see changes-since-PRC-poster.txt). For both the poster dataset and the current dataset, 5 items have 2 categories (see 5-items-have-2-categories.txt). Articles were selected from the Empirical Retraction Lit bibliography (https://infoqualitylab.org/projects/risrs2020/bibliography/ and https://doi.org/10.5281/zenodo.5498474 ). The current dataset includes 92 items; 91 items were selected from the 386 total items in Empirical Retraction Lit bibliography version v.2.15.0 (July 2021); 1 item was added because it is the final form publication of a grouping of 2 items from the bibliography: Yang (2022) Do retraction practices work effectively? Evidence from citations of psychological retracted articles http://doi.org/10.1177/01655515221097623 Items were classified into 7 topics; 2 of the 7 topics have been analyzed to date. ********************** OVERVIEW OF ANALYSIS ********************** DATA ANALYZED: 2 of the 7 topics have been analyzed to date: field-based case studies (n = 20) author-focused case studies of 1 or several authors with many retracted publications (n = 15) FUTURE DATA TO BE ANALYZED, NOT YET COVERED: 5 of the 7 topics have not yet been analyzed as of this release: database-focused analyses (n = 33) paper-focused case studies of 1 to 125 selected papers (n = 15) studies of retracted publications cited in review literature (n = 8) geographic case studies (n = 4) studies selecting retracted publications by method (n = 2) ************** FILE LISTING ************** ------------------ BIBLIOGRAPHY ------------------ 92-PRC-items.pdf ------------------ TEXT FILES ------------------ README.txt 5-items-have-2-categories.txt changes-since-PRC-poster.txt ------------------ CODEBOOKS ------------------ Codebook for authors.docx Codebook for authors.pdf Codebook for field.docx Codebook for field.pdf Codebook for KEY.docx Codebook for KEY.pdf ------------------ SPREADSHEETS ------------------ field.csv field.xlsx multipleauthors.csv multipleauthors.xlsx multipleauthors-not-named.csv multipleauthors-not-named.xlsx singleauthors.csv singleauthors.xlsx *************************** DESCRIPTION OF FILE TYPES *************************** BIBLIOGRAPHY (92-PRC-items.pdf) presents the items, as of the poster version. This has minor differences from the current data set. Consult changes-since-PRC-poster.txt for details on the differences. TEXT FILES provide notes for additional context. These files end in .txt. CODEBOOKS describe the data we collected. The same data is provided in both Word (.docx) and PDF format. There is one general codebook that is referred to in the other codebooks: Codebook for KEY lists fields assigned (e.g., for a journal or conference). Note that this is distinct from the overall analysis in the Empirical Retraction Lit bibliography of fields analyzed; for that analysis see Proescholdt, Randi (2021): RISRS Retraction Review - Field Variation Data. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2070560_V1 Other codebooks document specific information we entered on each column of a spreadsheet. SPREADSHEETS present the data collected. The same data is provided in both Excel (.xlsx) and CSV format. Each data row describes a publication or item (e.g., thesis, poster, preprint). For column header explainations, see the associated codebook. ***************************** DETAILS ON THE SPREADSHEETS ***************************** field-based case studies CODEBOOK: Codebook for field --REFERS TO: Codebook for KEY DATA SHEET: field REFERS TO: Codebook for KEY --NUMBER OF DATA ROWS: 20 NOTE: Each data row describes a publication/item. --NUMBER OF PUBLICATION GROUPINGS: 17 --GROUPED PUBLICATIONS: Rubbo (2019) - 2 items, Yang (2022) - 3 items author-focused case studies of 1 or several authors with many retracted publications CODEBOOK: Codebook for authors --REFERS TO: Codebook for KEY DATA SHEET 1: singleauthors (n = 9) --NUMBER OF DATA ROWS: 9 --NUMBER OF PUBLICATION GROUPINGS: 9 DATA SHEET 2: multipleauthors (n = 5 --NUMBER OF DATA ROWS: 5 --NUMBER OF PUBLICATION GROUPINGS: 5 DATA SHEET 3: multipleauthors-not-named (n = 1) --NUMBER OF DATA ROWS: 1 --NUMBER OF PUBLICATION GROUPINGS: 1 ********************************* CRediT <http://credit.niso.org> ********************************* Susmita Das: Conceptualization, Data curation, Investigation, Methodology Jaqueline Léveillé: Data curation, Investigation Randi Proescholdt: Conceptualization, Data curation, Investigation, Methodology Jodi Schneider: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Supervision
keywords:
retraction; citation of retracted publications; post-retraction citation; data extraction for scoping reviews; data extraction for literature reviews;