cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13012/b2idb-2773204_v1
title: Data for the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics

description: This repository contains the training dataset associated with the 2023 Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics (DGM-Image Challenge), hosted by the American Association of Physicists in Medicine. This dataset contains more than 100,000 8-bit images of size 512x512. These images emulate coronal slices from anthropomorphic breast phantoms adapted from the VICTRE toolchain [1], with assigned X-ray attenuation coefficients relevant for breast computed tomography. Please follow the instructions given on the following page in order to register for the challenge: https://www.aapm.org/GrandChallenge/DGM-Image/. 

[1] Badano, Aldo, et al. "Evaluation of digital breast tomosynthesis as replacement of full-field digital mammography using an in-silico imaging trial." JAMA network open 1.7 (2018): e185474-e185474
DOI: 10.6084/m9.figshare.21298842.v2
title: figure1&S1

description: figure1&S1
DOI: 10.6084/m9.figshare.24803139
title: H1_peaks2.BED

description: ATAC-seq
DOI: 10.6084/m9.figshare.24803139.v1
title: H1_peaks2.BED

description: ATAC-seq
DOI: 10.6084/m9.figshare.24803142
title: Sleep Health and Lifestyle Data Set (Part 2)

description: Dataset Overview:<br>The Sleep Health and Lifestyle Dataset comprises 400 rows and 13 columns, covering a wide range of variables related to sleep and daily habits. It includes details such as gender, age, occupation, sleep duration, quality of sleep, physical activity level, stress levels, BMI category, blood pressure, heart rate, daily steps, and the presence or absence of sleep disorders.Key Features of the Dataset:<br>Comprehensive Sleep Metrics: Explore sleep duration, quality, and factors influencing sleep patterns.<br>Lifestyle Factors: Analyze physical activity levels, stress levels, and BMI categories.<br>Cardiovascular Health: Examine blood pressure and heart rate measurements.<br>Sleep Disorder Analysis: Identify the occurrence of sleep disorders such as Insomnia and Sleep Apnea.Dataset Columns:<br>Person ID: An identifier for each individual.<br>Gender: The gender of the person (Male/Female).<br>Age: The age of the person in years.<br>Occupation: The occupation or profession of the person.<br>Sleep Duration (hours): The number of hours the person sleeps per day.<br>Quality of Sleep (scale: 1-10): A subjective rating of the quality of sleep, ranging from 1 to 10.<br>Physical Activity Level (minutes/day): The number of minutes the person engages in physical activity daily.<br>Stress Level (scale: 1-10): A subjective rating of the stress level experienced by the person, ranging from 1 to 10.<br>BMI Category: The BMI category of the person (e.g., Underweight, Normal, Overweight).<br>Blood Pressure (systolic/diastolic): The blood pressure measurement of the person, indicated as systolic pressure over diastolic pressure.<br>Heart Rate (bpm): The resting heart rate of the person in beats per minute.<br>Daily Steps: The number of steps the person takes per day.<br>Sleep Disorder: The presence or absence of a sleep disorder in the person (None, Insomnia, Sleep Apnea).Details about Sleep Disorder Column:None: The individual does not exhibit any specific sleep disorder.<br>Insomnia: The individual experiences difficulty falling asleep or staying asleep, leading to inadequate or poor-quality sleep.<br>Sleep Apnea: The individual suffers from pauses in breathing during sleep, resulting in disrupted sleep patterns and potential health risks.
DOI: 10.5281/zenodo.10373040
title: Pereira et al snakeworms iNaturalist obs_ Supplementary_File_2.csv

description: Pereira et al snakeworms iNaturalist observations_ Supplementary_File_2.csv
DOI: 10.5281/zenodo.10373039
title: Pereira et al snakeworms iNaturalist obs_ Supplementary_File_2.csv

description: Pereira et al snakeworms iNaturalist observations_ Supplementary_File_2.csv
DOI: 10.5517/ccdc.csd.cc2c652v
title: CCDC 2180666: Experimental Crystal Structure Determination

description: Related Article: Zhipeng Huo, Delin Min, Shijie Zhang, Mei-Lin Tang, Xun Sun|2023|RSC Med. Chem.|14|2738|doi:10.1039/D3MD00337J
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.cc2f7h17
title: CCDC 2241518: Experimental Crystal Structure Determination

description: Related Article: Mahmoud Al‐Refai, Basem F. Ali, Eman K. Al‐Masri, Iman A. Mansi, Nayyef Aljaar, Bashaer Abu‐Irmaileh, Armin Geyer, Sergei I. Ivlev|2023|J.Heterocycl.Chem.|60|2009|doi:10.1002/jhet.4732
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.cc2f7h28
title: CCDC 2241519: Experimental Crystal Structure Determination

description: Related Article: Mahmoud Al‐Refai, Basem F. Ali, Eman K. Al‐Masri, Iman A. Mansi, Nayyef Aljaar, Bashaer Abu‐Irmaileh, Armin Geyer, Sergei I. Ivlev|2023|J.Heterocycl.Chem.|60|2009|doi:10.1002/jhet.4732
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.cc2fx39s
title: CCDC 2261335: Experimental Crystal Structure Determination

description: Related Article: Pradip Pattanayak, Arnab Nandi, Pradipta Purkayastha|2023|Chem.Mater.|35|9799|doi:10.1021/acs.chemmater.3c02505
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.cc2ghsj9
title: CCDC 2279291: Experimental Crystal Structure Determination

description: Related Article: Guanping Li, Olaf Stefanczyk, Kunal Kumar, Kenta Imoto, Koji Nakabayashi, Shin-ichi Ohkoshi|2023|Chem.Mater.|35|9613|doi:10.1021/acs.chemmater.3c01756
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.cc2ghskb
title: CCDC 2279292: Experimental Crystal Structure Determination

description: Related Article: Guanping Li, Olaf Stefanczyk, Kunal Kumar, Kenta Imoto, Koji Nakabayashi, Shin-ichi Ohkoshi|2023|Chem.Mater.|35|9613|doi:10.1021/acs.chemmater.3c01756
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.cc2ghslc
title: CCDC 2279293: Experimental Crystal Structure Determination

description: Related Article: Guanping Li, Olaf Stefanczyk, Kunal Kumar, Kenta Imoto, Koji Nakabayashi, Shin-ichi Ohkoshi|2023|Chem.Mater.|35|9613|doi:10.1021/acs.chemmater.3c01756
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.cc2gkn0q
title: CCDC 2281073: Experimental Crystal Structure Determination

description: Related Article: Aleksandr Kazimir, Benedikt Schwarze, Peter Lönnecke, Sanja Jelača, Sanja Mijatović, Danijela Maksimović-Ivanić, Evamarie Hey-Hawkins|2023|RSC Med. Chem.|14|2574|doi:10.1039/D3MD00344B
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.cc2gylxy
title: CCDC 2292571: Experimental Crystal Structure Determination

description: Related Article: Douglas Turnbull, Marc-André Légaré|2023|Chemical Science|14|14256|doi:10.1039/D3SC05071H
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.cc2gylyz
title: CCDC 2292572: Experimental Crystal Structure Determination

description: Related Article: Douglas Turnbull, Marc-André Légaré|2023|Chemical Science|14|14256|doi:10.1039/D3SC05071H
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.cc2gylz0
title: CCDC 2292573: Experimental Crystal Structure Determination

description: Related Article: Douglas Turnbull, Marc-André Légaré|2023|Chemical Science|14|14256|doi:10.1039/D3SC05071H
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.cc2gym02
title: CCDC 2292574: Experimental Crystal Structure Determination

description: Related Article: Douglas Turnbull, Marc-André Légaré|2023|Chemical Science|14|14256|doi:10.1039/D3SC05071H
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.cc2gym13
title: CCDC 2292575: Experimental Crystal Structure Determination

description: Related Article: Douglas Turnbull, Marc-André Légaré|2023|Chemical Science|14|14256|doi:10.1039/D3SC05071H
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.cc2gym24
title: CCDC 2292576: Experimental Crystal Structure Determination

description: Related Article: Douglas Turnbull, Marc-André Légaré|2023|Chemical Science|14|14256|doi:10.1039/D3SC05071H
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.cc2gym35
title: CCDC 2292577: Experimental Crystal Structure Determination

description: Related Article: Douglas Turnbull, Marc-André Légaré|2023|Chemical Science|14|14256|doi:10.1039/D3SC05071H
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.cc2gym57
title: CCDC 2292579: Experimental Crystal Structure Determination

description: Related Article: Douglas Turnbull, Marc-André Légaré|2023|Chemical Science|14|14256|doi:10.1039/D3SC05071H
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.cc2gym68
title: CCDC 2292580: Experimental Crystal Structure Determination

description: Related Article: Douglas Turnbull, Marc-André Légaré|2023|Chemical Science|14|14256|doi:10.1039/D3SC05071H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.7262354
title: Raw Data and Scripts used in Regulation of single-cell heterogeneity of capsular polysaccharide synthesis in a human gut symbiont

description: Raw data used in this publication.  Single-cell analysis of promoter inversions reveals differential inversion rates as a determinant of bacterial population heterogeneity.


 


Libx.zip contains raw sequencing reads


scripts.zip contains code for analysis of reads and growth curve data


SequencingRawDataFilesIndex.xls contains a description of all the raw data in each libx.zip.
DOI: 10.5281/zenodo.7262353
title: Raw Data and Scripts used in Regulation of single-cell heterogeneity of capsular polysaccharide synthesis in a human gut symbiont

description: Raw data used in this publication.  Single-cell analysis of promoter inversions reveals differential inversion rates as a determinant of bacterial population heterogeneity.


 


Libx.zip contains raw sequencing reads


scripts.zip contains code for analysis of reads and growth curve data


SequencingRawDataFilesIndex.xls contains a description of all the raw data in each libx.zip.
DOI: 10.5281/zenodo.10372980
title: Exploring the Molecular Pathways of the Activation Process on PPARγ Recurrent Bladder  Cancer Mutants

description: The intricate involvement of Peroxisome Proliferator-Activated Receptor Gamma (PPARγ) in vital processes such as glucose homeostasis and adipogenesis is well established. However, its multifaceted role in cancer, particularly in luminal bladder cancer, remains a subject of intense debate. In this context, PPARγ’s overexpression and activation have been implicated in tumorigenesis. Notably, specific gain-of-function mutations (M280I, I290M, and T475M) within PPARγ’s ligand-binding domain have been pinpointed in bladder cancer, correlating with receptor activation. Nonetheless, the underlying molecular pathways prompted by these mutations remain obscure. Here, we employed a dual-basin structure-based model (db SBM) to unveil the intricate conformational dynamics that underlie the transition between PPARγ’s inactive and active states. Additionally, we explored the effects of the M280I, I290M, and T475M mutations on this pivotal process. Our findings concur with existing literature, revealing heightened ligand-independent transcriptional activity in the I290M and T475M mutants compared to other variants. Importantly, both mutants displayed enhanced stabilization of the active state relative to the wild-type receptor, and the I290M mutation promoted a remarkably specific transition route, rendering it a prime candidate for further investigation. Electrostatic analysis pinpointed the pivotal role of residues K303 and E488 in the activation cascade of I290M. This insight was substantiated by biophysical assays, as disruption of the K303-E488 interaction curtailed the thermal stabilization characteristic of the I290M mutation. These findings designate K303 and E488 as potential targets for inhibitors aimed at modulating PPARγ activation, with promising implications for refining bladder cancer prognosis. In sum, our study highlights the remarkable predictive capabilities achieved through the integration of simulation and cheminformatics methods, validated by biochemical experiments, to gain deeper insights into molecular mechanisms of activation and identify target residues for protein modulation.
DOI: 10.5281/zenodo.10372979
title: Exploring the Molecular Pathways of the Activation Process on PPARγ Recurrent Bladder  Cancer Mutants

description: The intricate involvement of Peroxisome Proliferator-Activated Receptor Gamma (PPARγ) in vital processes such as glucose homeostasis and adipogenesis is well established. However, its multifaceted role in cancer, particularly in luminal bladder cancer, remains a subject of intense debate. In this context, PPARγ’s overexpression and activation have been implicated in tumorigenesis. Notably, specific gain-of-function mutations (M280I, I290M, and T475M) within PPARγ’s ligand-binding domain have been pinpointed in bladder cancer, correlating with receptor activation. Nonetheless, the underlying molecular pathways prompted by these mutations remain obscure. Here, we employed a dual-basin structure-based model (db SBM) to unveil the intricate conformational dynamics that underlie the transition between PPARγ’s inactive and active states. Additionally, we explored the effects of the M280I, I290M, and T475M mutations on this pivotal process. Our findings concur with existing literature, revealing heightened ligand-independent transcriptional activity in the I290M and T475M mutants compared to other variants. Importantly, both mutants displayed enhanced stabilization of the active state relative to the wild-type receptor, and the I290M mutation promoted a remarkably specific transition route, rendering it a prime candidate for further investigation. Electrostatic analysis pinpointed the pivotal role of residues K303 and E488 in the activation cascade of I290M. This insight was substantiated by biophysical assays, as disruption of the K303-E488 interaction curtailed the thermal stabilization characteristic of the I290M mutation. These findings designate K303 and E488 as potential targets for inhibitors aimed at modulating PPARγ activation, with promising implications for refining bladder cancer prognosis. In sum, our study highlights the remarkable predictive capabilities achieved through the integration of simulation and cheminformatics methods, validated by biochemical experiments, to gain deeper insights into molecular mechanisms of activation and identify target residues for protein modulation.
DOI: 10.6073/pasta/ef0b914dbbb60d20466755dea95bf9bf
title: Discrete water temperature, flow, solar radiation, chlorophyll-a and inundation, Sacramento-San Joaquin Delta, CA, 1999-2019

description: The objective of our study is to better understand the factors affecting chlorophyll-a production within a floodplain and its transport downstream to determine how lateral connectivity influences longitudinal connectivity. The Yolo Bypass is an engineered floodplain of the Sacramento River that inundates during periods of high outflow via overtopping weirs. Water traveling through the Yolo Bypass flows parallel to the Sacramento River and re-connects to the mainstem at the southern extent of the floodplain. Several monitoring programs in the Sacramento San-Joaquin Delta and Yolo Bypass collect discrete and continuous water quality data, including chlorophyll measurements. For this study, we synthesized available flow, water temperature, chlorophyll and inundation data between March 1999 to December 2019 and modeled the effects of environmental variables and inundation on chlorophyll-a production in the floodplain, the mainstem, and downstream of the floodplain/mainstem.
DOI: 10.6084/m9.figshare.24803196.v1
title: BSDA_Speckle decorrelation OD=0.35&0.5 pH2&pH8

description: BSDA_Speckle decorrelation datasets. Speckle decorrelation curves of five bacteria under different conditions. OD=0.35&0.5 pH2&pH8. The bacteria are: L. acidophilus, L. gasseri, L. casei Shirota, L. plantarum, and 37 5AS.
DOI: 10.6084/m9.figshare.24803196.v2
title: BSDA_Speckle decorrelation OD=0.35&0.5 pH2&pH8

description: BSDA_Speckle decorrelation datasets. Speckle decorrelation curves of five bacteria under different conditions. OD=0.35&0.5 pH2&pH8. The bacteria are: L. acidophilus, L. gasseri, L. casei Shirota, L. plantarum, and 37 5AS.
DOI: 10.34740/kaggle/dsv/7195811
title: Daily Public Opinion on Israel-Palestine War
DOI: 10.6084/m9.figshare.19601689
title: Hydrogen Combustion using IRC, AIMD and normal modes

description: The generation of reference data for deep learning models is challenging for reactive systems, and more so for combustion reactions due to the extreme conditions that create radical species and alternative spin states during the combustion process. Here, we extend intrinsic reaction coordinate (IRC) calculations with <em>ab initio </em>Molecular dynamics (AIMD) simulations and normal mode displacement calculations to more extensively cover the potential energy surface for 19 key reaction channels involved in hydrogen combustion. A total of ~290,000 potential energies and ~1,260,000 nuclear force vectors are evaluated with a high quality range-separated hybrid density functional, ωB97X-V, to construct the reference data set, including transition state ensembles, for the deep learning models to study hydrogen combustion reaction.
DOI: 10.6084/m9.figshare.24803232
title: H1 peaks fixed

description: ATAC-seq
DOI: 10.6084/m9.figshare.24803232.v1
title: H1 peaks fixed

description: ATAC-seq
DOI: 10.15131/shef.data.23717859.v1
title: Charge superradiance on charged BTZ black holes

description: Data for the figures in the paper "Charge superradiance on charged BTZ black holes", arXiv:2301.01169 [hep-th]
DOI: 10.5517/ccdc.csd.cc2gym79
title: CCDC 2292581: Experimental Crystal Structure Determination

description: Related Article: Douglas Turnbull, Marc-André Légaré|2023|Chemical Science|14|14256|doi:10.1039/D3SC05071H
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.