cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.9751445
title: Additional file 8: of Combining next-generation sequencing and single-molecule sequencing to explore brown plant hopper responses to contrasting genotypes of japonica rice

description: Detection and CDS of novel genes. Tables S9. and S10: All 1794 predicted novel gene sequences and 2664 CDS sequences for these predicted novel genes, respectively. (XLSX 3266 kb)
DOI: 10.6084/m9.figshare.9751445.v1
title: Additional file 8: of Combining next-generation sequencing and single-molecule sequencing to explore brown plant hopper responses to contrasting genotypes of japonica rice

description: Detection and CDS of novel genes. Tables S9. and S10: All 1794 predicted novel gene sequences and 2664 CDS sequences for these predicted novel genes, respectively. (XLSX 3266 kb)
DOI: 10.6084/m9.figshare.9751448
title: Additional file 9: of Combining next-generation sequencing and single-molecule sequencing to explore brown plant hopper responses to contrasting genotypes of japonica rice

description: Functional annotations of novel genes in six databases: Nr, Swiss-Prot, KEGG, GO, RefSeq and COG. (XLSX 382 kb)
DOI: 10.6084/m9.figshare.9751448.v1
title: Additional file 9: of Combining next-generation sequencing and single-molecule sequencing to explore brown plant hopper responses to contrasting genotypes of japonica rice

description: Functional annotations of novel genes in six databases: Nr, Swiss-Prot, KEGG, GO, RefSeq and COG. (XLSX 382 kb)
DOI: 10.6084/m9.figshare.20236887
title: Cobalt–nickel layered double hydroxide on hollow Co<sub>3</sub>S<sub>4</sub>/CuS derived from ZIF-67 for efficient overall water splitting

description: Electrochemical water splitting is one of the most efficient strategies to generate clean energy H<sub>2</sub>. Herein, a novel hollow Co<sub>3</sub>S<sub>4</sub>/CuS@CoNi-LDH nanocomposite was designed. This hollow Co<sub>3</sub>S<sub>4</sub>/CuS@CoNi-LDH achieved OER overpotential of 220 mV, HER overpotential of 136 mV, respectively, at the current density of 10 mA cm<sup>−2</sup>. Notably, the hollow Co<sub>3</sub>S<sub>4</sub>/CuS@CoNi-LDH serving as both anode and cathode is assembled into a two-electrode water splitting device, and the potential of no more than 1.74 V is required to achieve the overall water splitting efficiency of 10 mA cm<sup>−2</sup>. This work provides a promising bifunctional catalyst for overall electrochemical water splitting.
DOI: 10.6084/m9.figshare.14993017
title: Additional file 7 of Global analysis of protein lysine 2-hydroxyisobutyrylation (Khib) profiles in Chinese herb rhubarb (Dahuang)

description: Table S6, Protein domain enrichment analysis of Khib-modified proteins
DOI: 10.6084/m9.figshare.12896667.v2
title: A Set of Efficient Methods to Generate High-Dimensional Binary Data With Specified Correlation Structures

description: High-dimensional correlated binary data arise in many areas, such as observed genetic variations in biomedical research. Data simulation can help researchers evaluate efficiency and explore properties of different computational and statistical methods. Also, some statistical methods, such as Monte Carlo methods, rely on data simulation. Lunn and Davies proposed linear time complexity methods to generate correlated binary variables with three common correlation structures. However, it is infeasible to specify unequal probabilities in their methods. In this article, we introduce several computationally efficient algorithms that generate high-dimensional binary data with specified correlation structures and unequal probabilities. Our algorithms have linear time complexity with respect to the dimension for three commonly studied correlation structures, namely exchangeable, decaying-product and <i>K</i>-dependent correlation structures. In addition, we extend our algorithms to generate binary data of specified nonnegative correlation matrices satisfying the validity condition with quadratic time complexity. We provide an R package, CorBin, to implement our simulation methods. Compared to the existing packages for binary data generation, the time cost to generate a 100-dimensional binary vector with the common correlation structures and general correlation matrices can be reduced up to 10<sup>5</sup> folds and 10<sup>3</sup> folds, respectively, and the efficiency can be further improved with the increase of dimensions. The R package CorBin is available on CRAN at https://cran.r-project.org/.
DOI: 10.6084/m9.figshare.12896667.v1
title: A set of efficient methods to generate high-dimensional binary data with specified correlation structures

description: High dimensional correlated binary data arise in many areas, such as observed genetic variations in biomedical research. Data simulation can help researchers evaluate efficiency and explore properties of different computational and statistical methods. Also, some statistical methods, such as Monte-Carlo methods, rely on data simulation. Lunn and Davies (1998) proposed linear time complexity methods to generate correlated binary variables with three common correlation structures. However, it is infeasible to specify unequal probabilities in their methods. In this manuscript, we introduce several computationally efficient algorithms that generate high-dimensional binary data with specified correlation structures and unequal probabilities. Our algorithms have linear time complexity with respect to the dimension for three commonly studied correlation structures, namely exchangeable, decaying-product and <i>K</i>-dependent correlation structures. In addition, we extend our algorithms to generate binary data of specified non-negative correlation matrices satisfying the validity condition with quadratic time complexity. We provide an R package, CorBin, to implement our simulation methods. Compared to the existing packages for binary data generation, the time cost to generate a 100-dimensional binary vector with the common correlation structures and general correlation matrices can be reduced up to 10<sup>5</sup> folds and 10<sup>3</sup> folds, respectively, and the efficiency can be further improved with the increase of dimensions. The R package CorBin is available on CRAN at https://cran.r-project.org/.
DOI: 10.6084/m9.figshare.12896667.v4
title: A Set of Efficient Methods to Generate High-Dimensional Binary Data With Specified Correlation Structures

description: High-dimensional correlated binary data arise in many areas, such as observed genetic variations in biomedical research. Data simulation can help researchers evaluate efficiency and explore properties of different computational and statistical methods. Also, some statistical methods, such as Monte Carlo methods, rely on data simulation. Lunn and Davies proposed linear time complexity methods to generate correlated binary variables with three common correlation structures. However, it is infeasible to specify unequal probabilities in their methods. In this article, we introduce several computationally efficient algorithms that generate high-dimensional binary data with specified correlation structures and unequal probabilities. Our algorithms have linear time complexity with respect to the dimension for three commonly studied correlation structures, namely exchangeable, decaying-product and <i>K</i>-dependent correlation structures. In addition, we extend our algorithms to generate binary data of specified nonnegative correlation matrices satisfying the validity condition with quadratic time complexity. We provide an R package, CorBin, to implement our simulation methods. Compared to the existing packages for binary data generation, the time cost to generate a 100-dimensional binary vector with the common correlation structures and general correlation matrices can be reduced up to 10<sup>5</sup> folds and 10<sup>3</sup> folds, respectively, and the efficiency can be further improved with the increase of dimensions. The R package CorBin is available on CRAN at https://cran.r-project.org/.
DOI: 10.6084/m9.figshare.21285416.v1
title: Efficacy and safety of liraglutide for obesity and people who are overweight: a systematic review and meta-analysis of randomized controlled trials

description: As the pandemic of obesity presents an increasing serious health challenge worldwide, additional medical interventions, especially pharmacotherapy, should be addressed for the affected people. Liraglutide 3.0 mg, is one of the possible options for long-term anti-obesity treatment. We systematically searched the databases of PubMed, Embase, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov. A meta-analysis was then performed using random-effect models. Meta-analyses of seven phase 3 and 4 RCTs (<i>N</i> = 6,028), which were conducted in adults with obesity or overweight for at least 1 year, demonstrated a significant weight reduction with liraglutide 3.0 mg (mean difference of percentage weight change −4.81%; 95% CI: −5.56% to −4.06%; <i>P</i> &lt; 0.00001), relative to placebo. However, more participants taking liraglutide experienced at least one adverse event. More discontinuations due to adverse events were observed among them. In the subgroup analysis among participants with or without diabetes mellitus (DM), pooled result showed that liraglutide was associated with a greater decrease in the percentage of weight change in participants without DM. This study provided support for the use of liraglutide 3.0 mg for weight management in adults with obesity or who are overweight.
DOI: 10.6084/m9.figshare.12896667.v3
title: A Set of Efficient Methods to Generate High-Dimensional Binary Data With Specified Correlation Structures

description: High-dimensional correlated binary data arise in many areas, such as observed genetic variations in biomedical research. Data simulation can help researchers evaluate efficiency and explore properties of different computational and statistical methods. Also, some statistical methods, such as Monte Carlo methods, rely on data simulation. Lunn and Davies proposed linear time complexity methods to generate correlated binary variables with three common correlation structures. However, it is infeasible to specify unequal probabilities in their methods. In this article, we introduce several computationally efficient algorithms that generate high-dimensional binary data with specified correlation structures and unequal probabilities. Our algorithms have linear time complexity with respect to the dimension for three commonly studied correlation structures, namely exchangeable, decaying-product and <i>K</i>-dependent correlation structures. In addition, we extend our algorithms to generate binary data of specified nonnegative correlation matrices satisfying the validity condition with quadratic time complexity. We provide an R package, CorBin, to implement our simulation methods. Compared to the existing packages for binary data generation, the time cost to generate a 100-dimensional binary vector with the common correlation structures and general correlation matrices can be reduced up to 10<sup>5</sup> folds and 10<sup>3</sup> folds, respectively, and the efficiency can be further improved with the increase of dimensions. The R package CorBin is available on CRAN at https://cran.r-project.org/.
DOI: 10.6084/m9.figshare.20236887.v1
title: Cobalt–nickel layered double hydroxide on hollow Co<sub>3</sub>S<sub>4</sub>/CuS derived from ZIF-67 for efficient overall water splitting

description: Electrochemical water splitting is one of the most efficient strategies to generate clean energy H<sub>2</sub>. Herein, a novel hollow Co<sub>3</sub>S<sub>4</sub>/CuS@CoNi-LDH nanocomposite was designed. This hollow Co<sub>3</sub>S<sub>4</sub>/CuS@CoNi-LDH achieved OER overpotential of 220 mV, HER overpotential of 136 mV, respectively, at the current density of 10 mA cm<sup>−2</sup>. Notably, the hollow Co<sub>3</sub>S<sub>4</sub>/CuS@CoNi-LDH serving as both anode and cathode is assembled into a two-electrode water splitting device, and the potential of no more than 1.74 V is required to achieve the overall water splitting efficiency of 10 mA cm<sup>−2</sup>. This work provides a promising bifunctional catalyst for overall electrochemical water splitting.
DOI: 10.6084/m9.figshare.11848377
title: Estimating the Covariance of Fragmented and Other Related Types of Functional Data

description: We consider the problem of estimating the covariance function of functional data which are only observed on a subset of their domain, such as fragments observed on small intervals or related types of functional data. We focus on situations where the data enable to compute the empirical covariance function or smooth versions of it only on a subset of its domain which contains a diagonal band. We show that estimating the covariance function consistently outside that subset is possible as long as the curves are sufficiently smooth. We establish conditions under which the covariance function is identifiable on its entire domain and propose a tensor product series approach for estimating it consistently. We derive asymptotic properties of our estimator and illustrate its finite sample properties on simulated and real data. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.25202252
title: SCC classification result on `character count &gt;= 26, line count &gt;= 2`

description: Code snippet language classificationSCC classification result on `character count &gt;= 26, line count &gt;= 2`
DOI: 10.6084/m9.figshare.11848377.v2
title: Estimating the Covariance of Fragmented and Other Related Types of Functional Data

description: We consider the problem of estimating the covariance function of functional data which are only observed on a subset of their domain, such as fragments observed on small intervals or related types of functional data. We focus on situations where the data enable to compute the empirical covariance function or smooth versions of it only on a subset of its domain which contains a diagonal band. We show that estimating the covariance function consistently outside that subset is possible as long as the curves are sufficiently smooth. We establish conditions under which the covariance function is identifiable on its entire domain and propose a tensor product series approach for estimating it consistently. We derive asymptotic properties of our estimator and illustrate its finite sample properties on simulated and real data. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.25202252.v2
title: scc_results

description: Code snippet language classification
DOI: 10.6084/m9.figshare.25202252.v3
title: SCC classification result on `character count &gt;= 26, line count &gt;= 2`

description: Code snippet language classificationSCC classification result on `character count &gt;= 26, line count &gt;= 2`
DOI: 10.6084/m9.figshare.14994155.v1
title: Relationship between diagnostic accuracy of microRNAs for NSCLC and number of combined microRNAs: an overview with meta-analysis

description: <b>Objective</b>: Several systematic reviews (SRs) have assessed the diagnostic accuracy of microRNAs (miRNAs) for NSCLC, and this overview aimed to assess the relationship between diagnostic accuracy of miRNAs for NSCLC and number of microRNAs combinations. <b>Methods</b>: Embase.com, PubMed, the Cochrane Library, and Web of Science were searched. The PRISMA-DTA was used for reporting quality evaluation. Meta-analysis was conducted to assess the pooled diagnostic accuracy of different miRNAs combinations, and subgroup analyses were performed based on the source of miRNA. <b>Results</b>: Fourteen SRs with 91 original studies were included. Three SRs had minimal reporting flaws, and 11 SRs had medium flaws. The pooled sensitivity and specificity were 0.76 and 0.80 for single miRNA, 0.80 and 0.81 for two miRNAs combined, 0.82 and 0.88 for three miRNAs combined, 0.88 and 0.92 for four miRNAs combined, 0.87 and 0.87 for five miRNAs combined, and 0.87 and 0.89 for six or more miRNAs combined. And miR-21 was mostly appeared. Subgroup analyses suggested that the serum-derived miRNA had the relatively best diagnostic value compared to other sources. <b>Conclusions</b>: Future studies should explore specific and serum-derived miRNAs in NSCLC and combine them to improve the diagnosis accuracy of NSCLC, which had great significance in economic efficiency.
DOI: 10.5281/zenodo.7861685
title: Synthesizing maximal unbiased benchmarking data for virtual screening via deep reinforcement learning

description: This compressed file contains all datasets made for the validation of MUBD<sup>syn</sup>. datasets_int_val: 17 cases in this folder are derived from MUBD for GPCRs (https://github.com/jwxia2014/ULS-UDS). MUBDreal was made by MUBD-DecoyMaker2.0 and MUBDsyn was made by MUBD-DecoyMaker<sup>syn</sup>. datasets_ext_val_classical_VS: Five cases in this folder are derived from the shared cases of MUV and DUD-E. The active sets of MUV were taken as the input to make corresponding MUBD datasets. Files in SBVS are raw molecular docking results by smina. datasets_ext_val_ML_VS: Ten cases in this folder are derived from NRLiSt-BDB. Corresponding MUBD datasets were made as described above. All these datasets can be used for the reproduction of validation performed in the manuscript or to benchmark various virtual screening methods.
DOI: 10.6084/m9.figshare.20236113.v1
title: Additional file 3 of Genome-wide analysis of citrus TCP transcription factors and their responses to abiotic stresses

description: Additional file 3: Table S2. Gene ontology (GO) of Citrus sinensis TCP genes.
DOI: 10.6084/m9.figshare.14994155.v2
title: Relationship between diagnostic accuracy of microRNAs for NSCLC and number of combined microRNAs: an overview with meta-analysis

description: <b>Objective</b>: Several systematic reviews (SRs) have assessed the diagnostic accuracy of microRNAs (miRNAs) for NSCLC, and this overview aimed to assess the relationship between diagnostic accuracy of miRNAs for NSCLC and number of microRNAs combinations. <b>Methods</b>: Embase.com, PubMed, the Cochrane Library, and Web of Science were searched. The PRISMA-DTA was used for reporting quality evaluation. Meta-analysis was conducted to assess the pooled diagnostic accuracy of different miRNAs combinations, and subgroup analyses were performed based on the source of miRNA. <b>Results</b>: Fourteen SRs with 91 original studies were included. Three SRs had minimal reporting flaws, and 11 SRs had medium flaws. The pooled sensitivity and specificity were 0.76 and 0.80 for single miRNA, 0.80 and 0.81 for two miRNAs combined, 0.82 and 0.88 for three miRNAs combined, 0.88 and 0.92 for four miRNAs combined, 0.87 and 0.87 for five miRNAs combined, and 0.87 and 0.89 for six or more miRNAs combined. And miR-21 was mostly appeared. Subgroup analyses suggested that the serum-derived miRNA had the relatively best diagnostic value compared to other sources. <b>Conclusions</b>: Future studies should explore specific and serum-derived miRNAs in NSCLC and combine them to improve the diagnosis accuracy of NSCLC, which had great significance in economic efficiency.
DOI: 10.6084/m9.figshare.9751487
title: MOESM1 of Function and mechanism of long non-coding RNA Gm21284 in the development of hippocampal cholinergic neurons

description: Additional file 1. The detailed results of Microarray.
DOI: 10.6084/m9.figshare.9751487.v1
title: MOESM1 of Function and mechanism of long non-coding RNA Gm21284 in the development of hippocampal cholinergic neurons

description: Additional file 1. The detailed results of Microarray.
DOI: 10.6084/m9.figshare.14994189.v2
title: Serum macrophage inhibitory cytokine-1 serves as a novel diagnostic biomarker of early-stage colorectal cancer

description: Patients with colorectal cancer usually have a poor prognosis because of the absence of suitable biomarkers for diagnosing asymptomatic patients. Here we determined the ability of MIC-1 to detect precancerous lesions and CRC in an asymptomatic cohort from CRC Screening Program. We screened 2759 subjects with risk factors. Endoscopic and histopathological analyses revealed that 19 and 47 subjects had CRC or precancerous lesions. We randomly selected 24 subjects with normal colonoscopies as healthy controls. We used receiver operating characteristic curve analysis to evaluate the diagnostic efficacy of MIC-1 for CRC and precancerous lesions. The optimal thresholds of MIC-1 levels with precancerous lesions or CRC were 314.12 pg/mL (sensitivity, 91.50%; specificity, 54.20%) and 357.64 pg/mL (sensitivity, 82.40%; specificity, 70.80%). Moreover, MIC-1 levels distinguished precancerous lesions better than CEA, CA19-9, or CA24-2 (AUC: 0.760 <i>vs.</i> 0.529, 0.624, and 0.585) or CRC (AUCs: 0.821 <i>vs.</i> 0.743, 0.657, and 0.688) from the healthy controls. The combination of MIC-1, CEA, CA19-9, and CA24-2 showed the highest in sensitivity and specificity for CRC diagnosis (sensitivity, 94.10%; specificity, 87.50%). Serum MIC-1 levels increased the sensitivity of detection of precancerous colorectal lesions and CRC and can be used to improve screening.
DOI: 10.6084/m9.figshare.7654193
title: Additional file 1: of Dynamic expression and functional analysis of circRNA in granulosa cells during follicular development in chicken

description: Table S1. Detailed information of primers used in this study. Table S2. All novel circRNAs detected in granulosa cells. Table S3. Flank intron length statistics. Table S4. Differentially expressed circRNAs (Fold change &gt;â 2, q-value &lt;â 0.05) in different granulosa cells. Table S5. Gene ontology for host genes of differential expressed circRNAs. Table S6. KEGG pathway for host genes of all differentially expressed circRNAs in three granulosa cells stage. Table S7. Overlapped prediction genes by TargetScan and miRDB. Table S8. Gene ontology of predicted target genes based on circRALGPS2. Table S9. KEGG pathway of predicted target genes based on circRALGPS2. (XLSX 1280 kb)
DOI: 10.5281/zenodo.7861684
title: Deep Reinforcement Learning Enables Better Bias Control in Benchmark for Virtual Screening

description: This compressed file contains all datasets made for the validation of MUBDsyn.

datasets_int_val: 17 cases in this folder are derived from MUBD for GPCRs. MUBDreal was made by MUBD-DecoyMaker2.0 and MUBDsyn was made by MUBD-DecoyMakersyn.
datasets_ext_val_classical_VS: Five cases in this folder are derived from the shared cases of MUV and DUD-E. The active sets of MUV were taken as the input to make corresponding MUBD datasets. Files in SBVS are raw molecular docking results by smina.
datasets_ext_val_SI_classical_VS: DeepCoy and TocoDecoy were used to make the datasets corresponding to the same five cases above. The data of DeepCoy was directly retrieved from DeepCoy resources at OPIG while topology decoys of TocoDecoy_9W were made based on the scripts provided at TocoDecoy GitHub Repository. Files in SBVS are raw molecular docking results by smina.
datasets_ext_val_ML_VS: Ten cases in this folder are derived from NRLiSt-BDB. Corresponding MUBD datasets were made as described above.
All these datasets can be used for the reproduction of validation performed in the manuscript or to benchmark various virtual screening methods.