cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/7pdr94m2hk.1
title: Supplementary Data for "CHASMplus reveals the scope of somatic missense mutations driving human cancers"

description: Large-scale cancer sequencing studies of patient cohorts have statistically implicated many cancer driver genes, with a long-tail of infrequently mutated genes. Here we present CHASMplus, a computational method to predict driver missense mutations, which is uniquely powered to identify rare driver mutations within the long-tail. We show that it substantially outperforms comparable methods across a wide variety of benchmark sets. Applied to 8,657 samples across 32 cancer types, CHASMplus identifies over 4,000 unique driver mutations in 240 genes, further distinguished by their specific cancer types. Our results support a prominent emerging role for rare driver mutations, with substantial variability in the frequency spectrum of drivers across cancer types. The trajectory of driver discovery may already be effectively saturated for certain cancer types, a finding with policy implications for future sequencing. As a resource to handle newly observed rare driver mutations, we systematically score every possible missense mutation across the genome. With the ever-growing pace of DNA sequencing of human tumors, the total number of detected mutations in cancer continues to accelerate. However, only a few mutations in each tumor may actually “drive” the growth of cancer, some of which can have value for diagnostic, prognostic, or therapeutic purposes. Based on a new rigorous statistical analysis of The Cancer Genome Atlas (TCGA), we find a prominent emerging role for rare missense mutations predicted to be “drivers” of cancer, which may have potential implications for genome-driven precision oncology, since rare driver mutations that are putatively actionable could be newly observed in a patient, thus, requiring personalized modeling and assessment. To extend beyond the TCGA, we provide a systematic resource to assess such newly observed missense mutations as cancer drivers. Lastly, we assess the driver landscape of human cancers and find that discovery for some cancer types are already approaching saturation. Detailed results of the manuscript "CHASMplus reveals the scope of somatic missense mutations driving human cancers" are provided in the following Supplementary Tables. Supplementary Table 1. Features used by CHASMplus. Supplementary Table S2. Driver somatic missense mutation results from pan-cancer analysis. Supplementary Table 3. Cancer type specific driver somatic missense mutation results Supplementary Table 4. Subtype enrichment for driver missense mutations predicted by CHASMplus Supplementary Table 5. Comparison of CHASMplus to saturation mutagenesis experiments of PTEN Supplementary Table 6. CHASMplus results on 1,013 prostate adenocarcinoma samples (Armenia et al.) Supplementary Table 7. Cancer type-specific driver somatic missense mutation results for skin cutaneous melanoma
DOI: 10.17632/8r6fg5hsz5.1
title: Solution Code: The Pricing of Sovereign Risk Under Costly Information

description: This file contains the fortran and matlab code used to solve the model in the paper "The Pricing of Sovereign Risk Under Costly Information."
DOI: 10.17632/b6bgtp9trh.1
title: ACP acylation is an acetyl-CoA-dependent modification required for electron transport chain assembly

description: Original images used to generate western blot figures.
DOI: 10.17632/mr39zgc7y5.1
title: Biomedical Event Extraction

description: See the details on https://github.com/cskyan/evntextrc#locate-the-pre-generated-dataset
DOI: 10.17632/zdmb4d9f8k.1
title: Raw Data

description: This file contains the raw data to simulate the macro and micro scale behaviors of polycrystalline materials. First, the related parameters to the macro domain are found. Second, the microscale parameters, including different numbers of grains, are included in order to be modeled.
DOI: 10.5281/zenodo.1404217
title: Evaluation Of Heracleum Sosnowskyi Manden. Survivial After Snow Cover Removing In Early Spring

description: The results of an experiment on the effect of snow cover removing on the areas occupied by Heracleum sosnowskyi stands in the early spring period. The experimental (impact) and control plots located in the Syktyvkar city suburb (Komi Republic, Russia).

Most of calculation were performed in R. Find the file "FrozenHogweed_R_script.r" for calculation reproducing.
DOI: 10.5281/zenodo.1404218
title: Evaluation Of Heracleum Sosnowskyi Manden. Survivial After Snow Cover Removing In Early Spring

description: The results of an experiment on the effect of snow cover removing on the areas occupied by Heracleum sosnowskyi stands in the early spring period. The experimental (impact) and control plots located in the Syktyvkar city suburb (Komi Republic, Russia).

Most of calculation were performed in R. Find the file "FrozenHogweed_R_script.r" for calculation reproducing.
DOI: 10.17632/7tn7n87mtb.1
title: Data set on the Estimate the emission from Cattle rearing from the Landmark University Farm.

description: Data set involve sub Categories of cattle in which estimation of feed Intake or Gross Energy (GE) Intake for Cattle Animal performance and diet data are required to estimate feed intake, which is the amount of energy (Mega Joules (MJ/day) an animal needs for maintenance and for activities, growth, lactation, work, and pregnancy. The method for Estimating methane emission from Enteric Fermentation using tier 2 methodology requires three basic steps: Step 1: Divide the livestock population into subcategory and characterize each sub-category (matured cow, Growing Heifers, Young Female, Mature male (Oxen), Breeding bull and Growing Male). Step 2: Estimate feed intake (gross energy) required for calculation of methane emission factor. Step 3: Calculate methane emission factors for each subcategory in terms of kilograms of methane per animal per year. Step 4: Multiply the subcategory emission factors by the subcategory populations to estimate subcategory emission Step 5: Sum-up the sub-category emission to get total emission from cattle
DOI: 10.17632/c6y2vfsgvk.1
title: Data set on the kinetics and Optimization of oil the extraction oil from algae.

description: The data set on the optimization and kinetics of oil extraction from microalgae (Chlorella Sp.) obtained in Landmark University commercial fish pond Omu-Aran, Kwara State. Algae biomass characterized using the photometer and Fourier transform infrared spectroscopy (FTIR) were presented in the data set. Oil from the algae was extracted using the Chemical method Extraction (N-hexane) with Soxhlet extractor unit. The optimization parameter performed was: solid–solvent ratio, moisture content, rate of drying algae paste, effect of time and temperature. The data set shows maximum oil yield of 31.50 % obtained with optimum condition of 6.6 % moisture content for a particle size of 2 to 3.30 mm, 60 0C temperatures solid to solvent ratio of 1:6 and 70 mins extraction time. The Kinetics reveals that this extraction followed first order model equation for the reaction time on oil yield with activation energy (Ea.) of 141.92KJ/mol.
DOI: 10.17632/fxj33nd36c.2
title: Dataset for validation of a Monte Carlo framework

description: Dataset usable to calibrate and validate a Monte Carlo framework for dosimetric applications in general projection radiology. The dataset includes: - the spectra - the measured radiation dose of the calibration and validation experiment - the material compositions used in the Monte Carlo framework
DOI: 10.17632/tvj5wc94nv.1
title: Willingness to pay Karimunjawa Visitor

description: The data set is willingness to pay of Karimunjawa visitors
DOI: 10.17632/28xzxjyspp.1
title: Selection of genes for ChIP-seq

description: This is to select ORFs with no overlapping transcriptional unit (on the same strand) 275 nt downstream the PAS. Protein-coding genes that do not overlap with any other transcription unit (on the opposite strand) in a region from 250 nt upstream to 500 nt downstream of the PAS were selected for the analysis.
DOI: 10.17632/3ygsn7pcyp.1
title: Identifying the Critical Success Factors of PPP Projects in China

description: PPP is a bridge to combine the strengths of the government and private sectors in order to deliver better infrastructure and services,thus, the government and private sectors both play a pivotal role in PPP projects, but the reasons for their participation are completely different. Their respective differences in interests lead government and private sectors to different perceptions as to what a “good” PPP project is, which causes their perceptive distinguished in their understandings of CSFs for PPP projects. This dataset is collected by questionnaires from civil servants and specialists in enterprises in Henan China, which represents the government and private sectors of PPP projects. It can be used to identify the conflict of interests and core contradictions in the current PPP projects by comparing the differences in perspective with respect to the critical success factors of PPP projects between the government and private sectors in China. SPSS 24.0 and Excel are the main software tools used for data analysis of the study. The statistical methods used included the Cronbach reliability test to determine the reliability of collected questionnaire information, the mean analysis compared the rank differences of 24 critical success factors between government and enterprises, the Kaisex-Meyer-Olkin (KMO) test, the Bartlett test, and factor analysis based on principal component analysis to reduce the dimension of the 24 critical success factors, which is helpful for summarizing the main influencing factors of PPP projects. The study results shows that there are differences in perspective with respect to four variables between the government and the private sectors in terms of the profitability of the project, sufficient political support, shorter life cycle and the operation and management experience of related projects, which reflects the shortcomings of the Chinese PPP model schemes in the preamble stage and the operation stage. Consequently, there are two unique contributions of this dataset:firstly,it offers a comparison of perception differences between the government and private sectors, which are the most important stakeholders of PPP projects. Secondly, by choosing Chinese PPP as the research object, this research not only attempts to identify the main hindrances to the development of PPP in China, but also to provide a theoretical and practical reference for PPP projects in the world.
DOI: 10.17632/h8vxj78pm9.1
title: Structural attributes, locational information and prices of more than 139 thousand apartment real estate listings in the city of Tehran (Iran)

description: The dataset contains structural attributes, locational information and prices for more than 139 thousand apartments in the city of Tehran (Iran). The data was collected from the largest national real estate website using a web crawler and contains submission date, exact location, neighborhood name, base area, floor level, age of building, price per square meter, and total price for the entries of the past four years.
DOI: 10.17632/p2c5vgsmk3.1
title: Expriemnts and results for manuscript "Existence and suppression of emotions towards algorithmic computer players in games"

description: This dataset includes screenshots, test subejcts' actions and payoffs, and also their answers to the questionnaires of the experiments done for our reseach project on emotions towards computer players. The corresponding manuscript is "Existence and suppression of emotions towards algorithmic computer players in games".
DOI: 10.17632/y7gnb79gfb.4
title: GEO Signature Extraction

description: See the details on https://github.com/cskyan/gesgnext#locate-the-pre-generated-dataset ****************************Supplementary Data**************************** Gene Set Enrichment Analysis Results - https://drive.google.com/drive/folders/1RsbCAh6dONp7xqLgLqtXV2EfGE2_16Im
DOI: 10.17632/zgw69pyzmy.1
title: Data required to reproduce the results

description: This file contains the data required to reproduce the macro and microscopic findings.
DOI: 10.17632/cjppyp5j3n.1
title: Supporting files for the ultraviolet room disinfection device.

description: Supporting files for the article "Programmable and low cost ultraviolet room disinfection device." APK file for the Android app which commands the device. AIA file contains the source code for the app which commands the device. It can be imported in MIT App Inventor 2 MP4 file contains a video showing the operation of the device. INO file contains the source code to program the Arduino UNO board of the device.
DOI: 10.17632/hjn9w7bm64.1
title: Image data for Cajigas et al. 2018 Mol Cell

description: FISH of single cell nuclei prepared from mouse E13.5 ganglionic eminence-derived interneuron progenitors. Combinations of different RNA/DNA and protein probes
DOI: 10.17632/sgxzbgw48b.1
title: Growth and population dynamic of Epinephelus fuscoguttatus

description: 1. Fish growth of Epinephelus fuscoguttatus from 10 and 15 cm in Karimunjawa Islands 2. Population dynamic of E. fuscoguttatus from 10 and 15 cm with several scenarios
DOI: 10.17632/wtzjf37pb7.2
title: CribRisks

description: Survey data for mothers who have babies in cribs. Responses include demographic variables and risk factors including having face covered by bedding, climbing out and falling from crib, hitting head on crib rails, and becoming entangled in crib slats.
DOI: 10.15472/dxalvq
title: Biodiversidad de la Reserva Natural de la Sociedad Civil Hacienda Portugal

description: Las Reservas Naturales de la Sociedad Civil (RNSC) contribuyen a la conservación de la diversidad biológica y gestión ambiental en los municipios donde están constituidas. La Hacienda Portugal se localiza sobre la vertiente occidental de la cordillera Central de los Andes colombianos, en la cuenca hidrográfica del río Cauca, específicamente en la cuenca del río La Vieja (municipio de Pereira, corregimiento de Cerritos); se encuentra entre los 1048 y 1198 msnm., con un área de 166.4 Ha. La información sobre Flora y Fauna consignada en este recurso proviene de los muestreos realizados para la Caracterización Ambiental de la Hacienda Portugal para el año 2007, resultante del convenio entre la Corporación Autónoma Regional de Risaralda (CARDER) y la Asociación Red Colombiana de Reservas Naturales de la Sociedad Civil (RESNATUR) (CARDER & RESNATUR, 2007).
DOI: 10.17632/4gm7xw6vc4.1
title: Characterization of Crimean wind farms placement
DOI: 10.17632/jbpwtjdmy3.1
title: CCndnS

description: This data set is for running simulation for NDN and mostly on my CCndnS caching policy. some data for random and popularity based caching policies are provided as well. The name of the folders indicates the cache size of each Content Store (CS). Depends on topology of the network (Abilene, Chained and Chained with branches), there are different set of source of content gnerators and content requesters. The measured values from client side is saved in a file with name ClinentX or Client_Rx. The data related to each router is presented in a file with the name of the router. For Abilene network, you can find the topology and the name of the routers in my paper. Be noted that in my paper routers' name starts from 1 (R1) but data files router name starts from 0. So R1 in the paper is R0 in the data set. There is one more file in each folder which provides the general information about the simulation like the cache size of each router, total Interests generated in the simulation or total network hit probability which is the probability of finding data from the network regardless of which router cached data. The name of some of the folders is like "alpha0.8". That means the parameter alpha for zipf distribution is set to 0.8 in this set of simulations. Folders with name "SLA" belongs to Service Level Agreement application that I explained in my paper. Many parameters can be found with value 0. These are parameters that I deactivated in this set of simulations but in general they can be measured. I used them for other studies.
DOI: 10.17632/w2n8273tgn.2
title: Data for: Numerical Investigation of Spatial and Temporal Structure of Annular Flow with Disturbance Waves

description: Entrainment and disturbance waves are simulated by VOF method. A systematic processing method is developed to accurately and efficiently calculate film thickness, which is the basis of calculation of wave parameter. By trying different values for the damping factor, B=20 is used since it could reasonably match the simulation with the experiment. This dataset shows the results obtained by B=20. Calculated film thickness is shown in two ways. One is z-t representation, which shows the result for each polar angle. These correspond to folders "z_t_raw" and "z_t_filtered", where "raw" denotes the original data, and "filtered" means a three-point median filter is used to remove fast droplets. In each folder, there are three subfolders which splits the 6s data evenly into three parts. The other way is theta-z representation where instantaneous film thickness distribution on the tube wall is shown for each saved time. A video, "B20.mp4", is made based on these figures. A FPS of 10 is used indicating that the video is 100 times slower than the real time.
DOI: 10.18169/papdeott007368
title: Computer-implementiertes Verfahren zur Erzeugung von Sensordaten
DOI: 10.17632/ycnx7zrhp7.1
title: Data for: Non-intrusive Load Composition Estimation for Low Voltage Substations from Aggregate ZIP Load Models

description: The dataset composes simulated aggregate Loads at low voltage distribution substation feeder. The data contains Pagg, Qagg, ZIP model of Pagg, ZIP model of Qagg, Voltage, Weight (Load Composition) and other derived parameters. The dataset was prepared as follows: 1. Load composition [0, 100%] among thirteen dominant load categories (at LV) using Monte-Carlo Simulation was generated. 2. Aggregate load at LV substantiation was prepared as the weighted sum of the generated load compositions and ZIP model of the contributing load categories.
DOI: 10.5281/zenodo.1405226
title: Data From The Brutus Python Package

description: Data downloaded from and pre-processed using the brutus python package.

 

<pre>If any of this data is used please make sure to cite:

Dua, D. and Karra Taniskidou, E. (2017). UCI Machine Learning Repository <strong>[http://archive.ics.uci.edu/ml]</strong>. Irvine, CA: University of California, School of Information and Computer Science. </pre>
DOI: 10.5281/zenodo.1405225
title: Data From The Brutus Python Package

description: Data downloaded from and pre-processed using the brutus python package.

 

<pre>If any of this data is used please make sure to cite:

Dua, D. and Karra Taniskidou, E. (2017). UCI Machine Learning Repository <strong>[http://archive.ics.uci.edu/ml]</strong>. Irvine, CA: University of California, School of Information and Computer Science. </pre>
DOI: 10.5517/ccdc.csd.cc1zhg20
title: CCDC 1832102: Experimental Crystal Structure Determination

description: Related Article: A. Makal|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|427|doi:10.1107/S2052520618010399
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: 10.5517/ccdc.csd.cc1zhg31
title: CCDC 1832103: Experimental Crystal Structure Determination

description: Related Article: A. Makal|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|427|doi:10.1107/S2052520618010399
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: 10.5517/ccdc.csd.cc1zhg42
title: CCDC 1832104: Experimental Crystal Structure Determination

description: Related Article: A. Makal|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|427|doi:10.1107/S2052520618010399
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: 10.5517/ccdc.csd.cc1zhg53
title: CCDC 1832105: Experimental Crystal Structure Determination

description: Related Article: A. Makal|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|427|doi:10.1107/S2052520618010399
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: 10.5517/ccdc.csd.cc1zjzxd
title: CCDC 1833585: Experimental Crystal Structure Determination

description: Related Article: B. Dittrich, F.P.A. Fabbiani, J. Henn, M.U. Schmidt, P. Macchi, K. Meindl, M.A. Spackman|2018|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|74|416|doi:10.1107/S2052520618010120
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: 10.5517/ccdc.csd.cc20jfss
title: CCDC 1862845: Experimental Crystal Structure Determination

description: Related Article: A.R. Badour, C.J. Arnett-Butscher, D.K. Mohanty, P.J. Squattrito, K.J. Lambright, K. Kirschbaum|2018|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|74|1038|doi:10.1107/S2053229618011737
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: 10.5517/ccdc.csd.cc20jftt
title: CCDC 1862846: Experimental Crystal Structure Determination

description: Related Article: A.R. Badour, C.J. Arnett-Butscher, D.K. Mohanty, P.J. Squattrito, K.J. Lambright, K. Kirschbaum|2018|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|74|1038|doi:10.1107/S2053229618011737
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.