cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24587802.v1
title: Additional file 2 of Disparities in spatially variable gene calling highlight the need for benchmarking spatial transcriptomics methods

description: Additional file 2: Table S1. Reported statistic and associated p-value from each combination of pairwise comparison of results between SpatialDE, SPARK-X, scGCO and Squidpy when reported p-values were compared using the Wilcoxon signed rank test. Table S2. Sensitivity and specificity of Squidpy, SPARK-X, SpatialDE and scGCO when used to analyse both simulated datasets generated with SRTsim. Sensitivity and specificity are reported over a range of q-value cut-offs, from 0.01-1.0. Table S3. Packages included for identification of SVGs in benchmarking study. The packages are ordered by assumptions made on distribution of gene expression. The rows highlighted in blue indicate grouped packages using graph-based methods. Table S4. Overview of publicly available 10X Visium datasets to be included in benchmarking process. FF indicates tissues that are fresh frozen and FFPE indicates tissues that are formalin-fixed paraffin-embedded. The filtered output files and imaging data from the Space Ranger v1.0.0, v1.2.0 or V1.3.0 pipeline were downloaded for each dataset.
DOI: 10.6084/m9.figshare.23972799
title: Additional file 2 of Training doctoral students in critical thinking and experimental design using problem-based learning

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.23972802
title: Additional file 3 of Training doctoral students in critical thinking and experimental design using problem-based learning

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.23972796.v1
title: Additional file 1 of Training doctoral students in critical thinking and experimental design using problem-based learning

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.23972802.v1
title: Additional file 3 of Training doctoral students in critical thinking and experimental design using problem-based learning

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.23972805.v1
title: Additional file 4 of Training doctoral students in critical thinking and experimental design using problem-based learning

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.23972796
title: Additional file 1 of Training doctoral students in critical thinking and experimental design using problem-based learning

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.23972799.v1
title: Additional file 2 of Training doctoral students in critical thinking and experimental design using problem-based learning

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.23972805
title: Additional file 4 of Training doctoral students in critical thinking and experimental design using problem-based learning

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.24587824
title: Additional file 4 of Increased paternal corticosterone exposure influences offspring behaviour and expression of urinary pheromones

description: Additional file 4: Submission experimental data. Data table with all the experimental data excluding sequencing results.
DOI: 10.6084/m9.figshare.24587824.v1
title: Additional file 4 of Increased paternal corticosterone exposure influences offspring behaviour and expression of urinary pheromones

description: Additional file 4: Submission experimental data. Data table with all the experimental data excluding sequencing results.
DOI: 10.6084/m9.figshare.24587826
title: Additional file 1 of Breast cancer patient-derived microtumors resemble tumor heterogeneity and enable protein-based stratification and functional validation of individualized drug treatment

description: Additional file 1: SI Materials 1. Antibodies used in DigiWest protein profiling analysis. Figure S1. Multicolor flow cytometry analysis of isolated and expanded TILs from BC specimen. Figure S2. Correlation of nuclear grade in PDM and PTT. Figure S3. Proteomic comparison of NST and ILC-derived BC PDM. Figure S4. Identification of resistance and sensitivity marker panels in treatment responder and non-responder microtumors and regression analysis of differently expressed proteins. Table S1. Clinical patient data of the patient cohort. Table S2. Descriptive statistics of “area” and “fluorescent intensity live/dead” measurements in PDM. Table S3. Raw data of DigiWest® protein signals in PDM and PTT samples and total measured protein amounts. Table S4. DigiWest®-based AFI protein signals in matched PDM-PTT pairs DigiWest®-based AFI protein signals in matched PDM-PTT pairs. Table S5. DigiWest®-based AFI protein signals of matched PDM-PTT pairs sorted by pathway affiliation. Table S6. Pearson correlation of protein abundances in PDM and corresponding PTT (PDM/PTT pairs). Table S7. DigIWest®-based AFI protein signals of n = 42 PDM samples. Table S8. Descriptive statistics of averaged, median-centered and log2 transformed protein signals for cell cycle, MAPK/RTK and PI3K/AKT pathway in n = 42 PDM samples. Table S9. Celltox™ Green assay RFU (relative fluorescent unit) values of BC microtumors treated with TAM, DTX, PTX and PAB. Table S10. Descriptive statistics of simple logistic regression analysis of differentially expressed proteins in treatment responder and non-responder groups.
DOI: 10.6084/m9.figshare.24587826.v1
title: Additional file 1 of Breast cancer patient-derived microtumors resemble tumor heterogeneity and enable protein-based stratification and functional validation of individualized drug treatment

description: Additional file 1: SI Materials 1. Antibodies used in DigiWest protein profiling analysis. Figure S1. Multicolor flow cytometry analysis of isolated and expanded TILs from BC specimen. Figure S2. Correlation of nuclear grade in PDM and PTT. Figure S3. Proteomic comparison of NST and ILC-derived BC PDM. Figure S4. Identification of resistance and sensitivity marker panels in treatment responder and non-responder microtumors and regression analysis of differently expressed proteins. Table S1. Clinical patient data of the patient cohort. Table S2. Descriptive statistics of “area” and “fluorescent intensity live/dead” measurements in PDM. Table S3. Raw data of DigiWest® protein signals in PDM and PTT samples and total measured protein amounts. Table S4. DigiWest®-based AFI protein signals in matched PDM-PTT pairs DigiWest®-based AFI protein signals in matched PDM-PTT pairs. Table S5. DigiWest®-based AFI protein signals of matched PDM-PTT pairs sorted by pathway affiliation. Table S6. Pearson correlation of protein abundances in PDM and corresponding PTT (PDM/PTT pairs). Table S7. DigIWest®-based AFI protein signals of n = 42 PDM samples. Table S8. Descriptive statistics of averaged, median-centered and log2 transformed protein signals for cell cycle, MAPK/RTK and PI3K/AKT pathway in n = 42 PDM samples. Table S9. Celltox™ Green assay RFU (relative fluorescent unit) values of BC microtumors treated with TAM, DTX, PTX and PAB. Table S10. Descriptive statistics of simple logistic regression analysis of differentially expressed proteins in treatment responder and non-responder groups.
DOI: 10.6084/m9.figshare.24054283.v1
title: Additional file 1 of Comparison of cognitive functional therapy and movement system impairment treatment in chronic low back pain patients: a randomized controlled trial

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.24054283
title: Additional file 1 of Comparison of cognitive functional therapy and movement system impairment treatment in chronic low back pain patients: a randomized controlled trial

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.23961958.v1
title: Additional file 1 of Identification of adipose tissue transcriptomic memory of anorexia nervosa

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.23961958
title: Additional file 1 of Identification of adipose tissue transcriptomic memory of anorexia nervosa

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.24587884
title: Additional file 1 of Genetic diversity and natural selection of Plasmodium vivax reticulocyte invasion genes in Ecuador

description: Additional file 1: Table S1. Diversity and genetic differentiation in pvdbpII among Ecuadorian locations.
DOI: 10.6084/m9.figshare.24587884.v1
title: Additional file 1 of Genetic diversity and natural selection of Plasmodium vivax reticulocyte invasion genes in Ecuador

description: Additional file 1: Table S1. Diversity and genetic differentiation in pvdbpII among Ecuadorian locations.
DOI: 10.6084/m9.figshare.24587887
title: Additional file 2 of Genetic diversity and natural selection of Plasmodium vivax reticulocyte invasion genes in Ecuador

description: Additional file 2: Table S2. Diversity and genetic differentiation in pvrbp1a-2 among Ecuadorian locations.
DOI: 10.6084/m9.figshare.24587887.v1
title: Additional file 2 of Genetic diversity and natural selection of Plasmodium vivax reticulocyte invasion genes in Ecuador

description: Additional file 2: Table S2. Diversity and genetic differentiation in pvrbp1a-2 among Ecuadorian locations.
DOI: 10.6084/m9.figshare.24587890.v1
title: Additional file 3 of Genetic diversity and natural selection of Plasmodium vivax reticulocyte invasion genes in Ecuador

description: Additional file 3: Table S3. Diversity and genetic differentiation in pvama1 among Ecuadorian locations.
DOI: 10.6084/m9.figshare.24587890
title: Additional file 3 of Genetic diversity and natural selection of Plasmodium vivax reticulocyte invasion genes in Ecuador

description: Additional file 3: Table S3. Diversity and genetic differentiation in pvama1 among Ecuadorian locations.
DOI: 10.6084/m9.figshare.24587893
title: Additional file 4 of Genetic diversity and natural selection of Plasmodium vivax reticulocyte invasion genes in Ecuador

description: Additional file 4: Table S4. Genetic diversity among pvama1 domains in Ecuadorian samples.
DOI: 10.6084/m9.figshare.24587893.v1
title: Additional file 4 of Genetic diversity and natural selection of Plasmodium vivax reticulocyte invasion genes in Ecuador

description: Additional file 4: Table S4. Genetic diversity among pvama1 domains in Ecuadorian samples.
DOI: 10.6084/m9.figshare.24587896
title: Additional file 5 of Genetic diversity and natural selection of Plasmodium vivax reticulocyte invasion genes in Ecuador

description: Additional file 5: Table S5. Polymorphisms associated with predicted linear B-cell epitopes in PvAMA1 among Ecuadorian samples.
DOI: 10.6084/m9.figshare.24587896.v1
title: Additional file 5 of Genetic diversity and natural selection of Plasmodium vivax reticulocyte invasion genes in Ecuador

description: Additional file 5: Table S5. Polymorphisms associated with predicted linear B-cell epitopes in PvAMA1 among Ecuadorian samples.
DOI: 10.6084/m9.figshare.24587829
title: Data rb.xlsx

description: In this study, the digital literacy levels of science teachers in different areas such as information management, communication, digital content creation, and online security were evaluated using the ‘Digital Literacy Scale’ questionnaire and a performance-weighted scoring approach as well as machine learning methods.
DOI: 10.6084/m9.figshare.24587775.v1
title: raw_data.xlsx

description: Waveguide lattices offer a compact and stable platform for a range of applications, including quantum walks, topological effects, condensed matter system simulation, and classical and quantum information processing. In such lattices, the Hamiltonian's hopping and on-site terms determine the optical evolution, which can be engineered using waveguide spacing and refractive index profile. While waveguide lattices have been realized in various photonic platforms, these devices have always been static and designed for specific applications. We present a programmable waveguide array in which the Hamiltonian terms can be electro-optically tuned to implement various Hamiltonian continuous-time evolutions on a single device. We used a single array with 11 waveguides in lithium niobate, controlled via 22 electrodes, to perform a range of experiments that realized the Su-Schriffer-Heeger model, the Aubrey-Andre model, and Anderson localization, which is equivalent to over 2500 static devices. Our architecture's micron-scale local electric fields independently control waveguide coupling coefficients and effective indices, which overcomes cross-talk limitations of thermo-optic phase shifters in other platforms such as silicon, silicon-nitride, and silica. Electro-optic control allows for ultra-fast and more precise reconfigurability with lower power consumption, and with quantum input states, our platform can enable the study of multiple condensed matter quantum dynamics with a single device.
DOI: 10.6084/m9.figshare.24587909
title: Additional file 2 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 2: Table S1. Total differentially expressed miRNAs in GBC and normal tissues.
DOI: 10.6084/m9.figshare.24587909.v1
title: Additional file 2 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 2: Table S1. Total differentially expressed miRNAs in GBC and normal tissues.
DOI: 10.6084/m9.figshare.24587912
title: Additional file 3 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 3: Table S2. The 131 GBC-related DE-miRNAs.
DOI: 10.6084/m9.figshare.24587912.v1
title: Additional file 3 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 3: Table S2. The 131 GBC-related DE-miRNAs.
DOI: 10.6084/m9.figshare.24587915
title: Additional file 4 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 4: Table S3.The miRNA enrichment analysis results of dysregulated miRNAs.
DOI: 10.6084/m9.figshare.24587915.v1
title: Additional file 4 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 4: Table S3.The miRNA enrichment analysis results of dysregulated miRNAs.
DOI: 10.6084/m9.figshare.24587918
title: Additional file 5 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 5: Table S4. The ceRNA network of GBC containing 211 mRNAs, 1 miRNA, 2 lncRNAs, and 48 circRNAs.
DOI: 10.6084/m9.figshare.24587918.v1
title: Additional file 5 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 5: Table S4. The ceRNA network of GBC containing 211 mRNAs, 1 miRNA, 2 lncRNAs, and 48 circRNAs.
DOI: 10.6084/m9.figshare.24587921.v1
title: Additional file 6 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 6: Table S5. Eighty biological process entries analysis of ceRNA regulatory network.
DOI: 10.6084/m9.figshare.24587924.v1
title: Additional file 7 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 7: Table S6. Twenty-one cellular components analysis of ceRNA regulatory network.
DOI: 10.6084/m9.figshare.24587927
title: Additional file 8 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 8: Table S7. Five molecular functions entries analysis of ceRNA regulatory network.
DOI: 10.6084/m9.figshare.24587921
title: Additional file 6 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 6: Table S5. Eighty biological process entries analysis of ceRNA regulatory network.
DOI: 10.6084/m9.figshare.24587924
title: Additional file 7 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 7: Table S6. Twenty-one cellular components analysis of ceRNA regulatory network.
DOI: 10.6084/m9.figshare.24587927.v1
title: Additional file 8 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 8: Table S7. Five molecular functions entries analysis of ceRNA regulatory network.
DOI: 10.6084/m9.figshare.24587930
title: Additional file 9 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 9: Table S8. One KEGG pathway analysis of ceRNA regulatory network.
DOI: 10.6084/m9.figshare.24587930.v1
title: Additional file 9 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 9: Table S8. One KEGG pathway analysis of ceRNA regulatory network.
DOI: 10.6084/m9.figshare.24587933
title: Additional file 10 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 10: Table S9. The potential effects of EOMES, FOXA1, FOXH1, OTX2, REST on GBC by regulating hsa-miR-4770.
DOI: 10.6084/m9.figshare.24587933.v1
title: Additional file 10 of Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

description: Additional file 10: Table S9. The potential effects of EOMES, FOXA1, FOXH1, OTX2, REST on GBC by regulating hsa-miR-4770.
DOI: 10.6084/m9.figshare.23983340.v1
title: Additional file 2 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.23983343.v1
title: Additional file 3 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.23983349
title: Additional file 5 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 5
DOI: 10.6084/m9.figshare.23983349.v1
title: Additional file 5 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 5
DOI: 10.6084/m9.figshare.23983340
title: Additional file 2 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.23983535
title: Additional file 7 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 7
DOI: 10.6084/m9.figshare.23983352.v1
title: Additional file 6 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.23983337
title: Additional file 1 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.23983346
title: Additional file 4 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.23983346.v1
title: Additional file 4 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.23983535.v1
title: Additional file 7 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 7
DOI: 10.6084/m9.figshare.24587775
title: raw_data.xlsx

description: Waveguide lattices offer a compact and stable platform for a range of applications, including quantum walks, topological effects, condensed matter system simulation, and classical and quantum information processing. In such lattices, the Hamiltonian's hopping and on-site terms determine the optical evolution, which can be engineered using waveguide spacing and refractive index profile. While waveguide lattices have been realized in various photonic platforms, these devices have always been static and designed for specific applications. We present a programmable waveguide array in which the Hamiltonian terms can be electro-optically tuned to implement various Hamiltonian continuous-time evolutions on a single device. We used a single array with 11 waveguides in lithium niobate, controlled via 22 electrodes, to perform a range of experiments that realized the Su-Schriffer-Heeger model, the Aubrey-Andre model, and Anderson localization, which is equivalent to over 2500 static devices. Our architecture's micron-scale local electric fields independently control waveguide coupling coefficients and effective indices, which overcomes cross-talk limitations of thermo-optic phase shifters in other platforms such as silicon, silicon-nitride, and silica. Electro-optic control allows for ultra-fast and more precise reconfigurability with lower power consumption, and with quantum input states, our platform can enable the study of multiple condensed matter quantum dynamics with a single device.
DOI: 10.6084/m9.figshare.24587775.v2
title: raw_data.xlsx

description: Waveguide lattices offer a compact and stable platform for a range of applications, including quantum walks, topological effects, condensed matter system simulation, and classical and quantum information processing. In such lattices, the Hamiltonian's hopping and on-site terms determine the optical evolution, which can be engineered using waveguide spacing and refractive index profile. While waveguide lattices have been realized in various photonic platforms, these devices have always been static and designed for specific applications. We present a programmable waveguide array in which the Hamiltonian terms can be electro-optically tuned to implement various Hamiltonian continuous-time evolutions on a single device. We used a single array with 11 waveguides in lithium niobate, controlled via 22 electrodes, to perform a range of experiments that realized the Su-Schriffer-Heeger model, the Aubrey-Andre model, and Anderson localization, which is equivalent to over 2500 static devices. Our architecture's micron-scale local electric fields independently control waveguide coupling coefficients and effective indices, which overcomes cross-talk limitations of thermo-optic phase shifters in other platforms such as silicon, silicon-nitride, and silica. Electro-optic control allows for ultra-fast and more precise reconfigurability with lower power consumption, and with quantum input states, our platform can enable the study of multiple condensed matter quantum dynamics with a single device.
DOI: 10.6084/m9.figshare.23983538
title: Additional file 8 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 8
DOI: 10.6084/m9.figshare.23983538.v1
title: Additional file 8 of Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

description: Supplementary Material 8
DOI: 10.25582/data.2024-04.3088238/2555184
title: Data for EMSL Project 60201 from April 2024
DOI: 10.5281/zenodo.15208263
title: Collatz conjecture
DOI: 10.5281/zenodo.15208264
title: Collatz conjecture
DOI: 10.25582/data.2024-04.3088304/2555185
title: Data for EMSL Project 60201 from April 2024
DOI: 10.25582/data.2024-04.3088320/2555186
title: Data for EMSL Project 60201 from April 2024
DOI: 10.25582/data.2024-04.3088489/2555187
title: Data for EMSL Project 60201 from April 2024