cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3981155
title: Data set for validation of a Python script for computation of Protein-Ligand Interaction Fingerprints

description: <strong>Data set for for validation of the Protein-Ligand Interaction Fingerprints, which includes examples of protein structures (original PDB and equilibrated) and molecular dynamics trajectories (equilibration and ligand dissociation generated using Random Acceleration MD simulations, RAMD)</strong> <strong>mdifp_validation_data.tar.gz - </strong>archive that contains benchmark dataset for evaluation of the protein-ligand IFP protocol (PDB structures of protonated complexes, ligands, and MOL2 files of ligands) published in D. B. Kokha, B. Doser, S. Richter, F. Ormersbach, X. Cheng, R. C. Wade "A Workflow for Exploring Ligand Dissociation from a Macromolecule: Efficient Random Acceleration Molecular Dynamics Simulation and Interaction Fingerprints Analysis of Ligand Trajectories" (2020) arXiv:2006.11066 <strong>2YKI </strong>- protein-ligand complex , PDB ID 2YKI<br> - 2yki_MOE.pdb complex with hydrogen added and energy minimized using MOE software (https://www.chemcomp.com/)<br> - ligand_2yki_MOE.mol2 and ligand_2yki_MOE.pdb - ligand structure with hydrogens prepered by MOE software (https://www.chemcomp.com/) <strong>6EI5</strong> - MD trajectory of the protein-ligand complex generated from PDB ID 6EI5<br> - ref-min.pdb minimized structure<br> - ref.prmtop topology file<br> - moe.mol2 - ligand structure in mol2 format<br> - amber2namd2.dcd generated MD trajectory <strong>SAD_3-RAMD-03-2020.pkl </strong>- a pkl dataset with IFPs generated from RAMD dissociation trajectory of the complex PDB ID: 5LQ9 (trajectories from the paper Front. Mol. Biosci., 2019 DOI:10.3389/fmolb.2019.00036) <strong>HSP90_Gromacs.zip </strong>- an archive that contains three pkl data sets of protein-ligand IFPs (for three HSP90 complexes; PDB ID: 5J64, 5J86, 5LQ9) generated from RAMD dissociation trajectories simulated using new Gromacs-RAMD engine (https://github.com/HITS-MCM/gromacs-ramd) The rest of the files contains data obtained from simulation of the complex of <strong>GPCR muscarinic receptor M2 (PDB ID:4MQT);</strong> immersed in a mixed membrane: 50% CHL, 30% POPC, 20% POPE) with a small molecule agonist iperoxo. <br> - <strong>IXO.pdb and moe.mol2 </strong>- PDBand MOL2 structure of iperoxo<br> - <strong>AMBER_eq.tar.gz</strong> - structure of the equilibrated complex generated using AMBER software<br> -<strong> NAMD_eq.tar.gz </strong>- two equilibration trajectories in dcd format generated using NAMD software <br> - <strong>RAMD_eq.tar.gz </strong>- dissociation tarjectoris of iprtoxo from the M2 protein generated from the last snapshot of two NAMD equilibration trajectories (for each case 2 RAMD dissociaiton trajectories are available)
DOI: 10.26165/juelich-data/gcbnma/89gwqd
title: elpv-dataset-master.zip

description: Zip-file of repository
DOI: 10.15468/mmusk6
title: Revalidation of Enteromius alberti and presence of Enteromius cf. mimus (Cypriniformes: Cyprinidae) in the Lake Edward system, East Africa

description: This dataset contains the digitized treatments in Plazi based on the original journal article Maetens, Heleen, Steenberge, Maarten Van, Snoeks, Jos, Decru, Eva (2020): Revalidation of Enteromius alberti and presence of Enteromius cf. mimus (Cypriniformes: Cyprinidae) in the Lake Edward system, East Africa. European Journal of Taxonomy 700: 1-28, DOI: http://doi.org/10.5852/ejt.2020.700
DOI: 10.6073/pasta/510de0ee18750619c160efd857211700
title: Vegetation data collected from Northeast Shark River Slough, Everglades National Park, Florida, from September 2006 to present

description: This project was established in 2006 to document the pattern of abundance of key ecological indicators (e.g., surface water, soil, floc, periphyton and sawgrass) across the NESRS landscape (Gaiser et al. 2009). A total of 30 sites were established and monitored in 2006, 2007 and 2008 . After the completion of 1-mile bridge in 2012, additional 10 new sites were established to observe the ecological impact of 1-mile bridge ( Known as Bridge & Census sites). In 2015, additional 40 sites were established along eight transects (T1-T8, known as near canal sites) in ENP marshes starting at, and roughly perpendicular to the L-29 canal. The purpose of these sites was to monitor the potential effects of Modified Water Deliveries (MWD) operations on changing nutrient concentrations and ratios in key ecological compartments due to increased downstream discharges from the L-29 canal beneath the 1-mile and 2.6-mile bridges and culverts along Tamiami Trail.
DOI: 10.21227/rsfg-7f09
title: Validation of a Velostat-Based Pressure Sensitive Mat for Center of Pressure Measurements. Dataset.

description: This dataset presents the measurements corresponding to the article "Validation of a Velostat-Based Pressure Sensitive Mat for Center of Pressure Measurements". You will find the data corresponding to an affordable commercial mat, a Velostat-based mat prototype, and a commercial force platform. The results obtained in the above-mentioned article can be reproduced with them. In the article there is a set of experiments involving people standing on these platforms simultaneously and the center-of-pressure (CoP) path was analyzed by extracting standard deviation along the axes and mean radius.In this dataset you can find the CoP displacement obtained by the software of the force platform, which are along with the measurements extracted from the commercial mat software, the raw data of the Velostat-Based prototype, and the post-processed data from the Velostat-Based prototype. The scripts section also includes the code to extract the CoP from the mat pressure maps, the post-processing of the prototype pressure maps, the computation of the standard deviation along the axes and mean radius. Besides, it prints on the screen a table with the summary of this computation.
DOI: 10.5281/zenodo.3981175
title: Pictogramas ARASAAC Color, Part 12 of 16

description: Black and white pictograms created by Sergio Palao (http://www.palao.es) for ARASAAC (http://www.arasac.org).
DOI: 10.5281/zenodo.3981174
title: Pictogramas ARASAAC Color, Part 12 of 16

description: Black and white pictograms created by Sergio Palao (http://www.palao.es) for ARASAAC (http://www.arasac.org).
DOI: 10.5517/cc13cg75
title: CCDC 1023906: Experimental Crystal Structure Determination

description: Related Article: M.A. Affan, Y.Z. Liew, B.A. Fasihuddin, M. Shamsuddin and M.Y. Bohari|2009|ACGC Chem.Res.Commun.|23|5|
DOI: 10.5517/cc13cgsq
title: CCDC 1023923: Experimental Crystal Structure Determination

description: Related Article: Sun Yingji|2009|Nankai Daxue Xuebao,Ziran Kexueban|42|54|
DOI: 10.5517/ccdc.csd.cc23wysr
title: CCDC 1963285: Experimental Crystal Structure Determination

description: Related Article: Zhiwen Tan, Jian Zhou, Tingting Jiang, Hua-Hong Zou, Lianshe Fu|2020|Dyes Pigm.|182|108638|doi:10.1016/j.dyepig.2020.108638
DOI: 10.5517/ccdc.csd.cc23wyts
title: CCDC 1963286: Experimental Crystal Structure Determination

description: Related Article: Zhiwen Tan, Jian Zhou, Tingting Jiang, Hua-Hong Zou, Lianshe Fu|2020|Dyes Pigm.|182|108638|doi:10.1016/j.dyepig.2020.108638
DOI: 10.5517/ccdc.csd.cc227zw6
title: CCDC 1914308: Experimental Crystal Structure Determination

description: Related Article: Ji Yang, Jun Wu, Jianhan Ye, Chaozong Wang, Mingyu Zheng, Xueyi Tong, Tingting Miao, Qian Shi|2019|Asian J.Org.Chem|8|1846|doi:10.1002/ajoc.201900365
DOI: 10.5517/ccdc.csd.cc246dh8
title: CCDC 1972359: Experimental Crystal Structure Determination

description: Related Article: Kapil Mohan Saini, Rakesh K. Saunthwal, Sushmita, Akhilesh K. Verma|2020|Org.Biomol.Chem.|18|5594|doi:10.1039/D0OB01281E
DOI: 10.5517/ccdc.csd.cc24bcgb
title: CCDC 1976171: Experimental Crystal Structure Determination

description: Related Article: Nutcha Ponjan, Filip Kielar, Winya Dungkaew, Kanokwan Kongpatpanich, Hikaru Zenno, Shinya Hayami, Mongkol Sukwattanasinitt, Kittipong Chainok|2020|CrystEngComm|22|4833|doi:10.1039/D0CE00099J
DOI: 10.5517/ccdc.csd.cc24bchc
title: CCDC 1976172: Experimental Crystal Structure Determination

description: Related Article: Nutcha Ponjan, Filip Kielar, Winya Dungkaew, Kanokwan Kongpatpanich, Hikaru Zenno, Shinya Hayami, Mongkol Sukwattanasinitt, Kittipong Chainok|2020|CrystEngComm|22|4833|doi:10.1039/D0CE00099J
DOI: 10.5517/ccdc.csd.cc23rs2r
title: CCDC 1959264: Experimental Crystal Structure Determination

description: Related Article: Nutcha Ponjan, Filip Kielar, Winya Dungkaew, Kanokwan Kongpatpanich, Hikaru Zenno, Shinya Hayami, Mongkol Sukwattanasinitt, Kittipong Chainok|2020|CrystEngComm|22|4833|doi:10.1039/D0CE00099J
DOI: 10.5517/ccdc.csd.cc24dmbj
title: CCDC 1978337: Experimental Crystal Structure Determination

description: Related Article: Di Luo, Ji-Zhao Xie, Lu-Hui Zou, Li Qiu, Dong-Ping Huang, Yun-Feng Xie, Huan-Ji Xu, Xin-Duo Wu|2020|Phytochemistry|177|112453|doi:10.1016/j.phytochem.2020.112453
DOI: 10.5517/ccdc.csd.cc24dmdl
title: CCDC 1978339: Experimental Crystal Structure Determination

description: Related Article: Di Luo, Ji-Zhao Xie, Lu-Hui Zou, Li Qiu, Dong-Ping Huang, Yun-Feng Xie, Huan-Ji Xu, Xin-Duo Wu|2020|Phytochemistry|177|112453|doi:10.1016/j.phytochem.2020.112453
DOI: 10.5517/ccdc.csd.cc24dmjq
title: CCDC 1978343: Experimental Crystal Structure Determination

description: Related Article: Di Luo, Ji-Zhao Xie, Lu-Hui Zou, Li Qiu, Dong-Ping Huang, Yun-Feng Xie, Huan-Ji Xu, Xin-Duo Wu|2020|Phytochemistry|177|112453|doi:10.1016/j.phytochem.2020.112453
DOI: 10.5517/ccdc.csd.cc24fdww
title: CCDC 1979098: Experimental Crystal Structure Determination

description: Related Article: Shaozhan Shi, Shui Yu, Lixia Quan, Majid Mansoor, Zilu Chen, Huancheng Hu, Dongcheng Liu, Yuning Liang, Fupei Liang|2020|J.Inorg.Biochem.|210|111173|doi:10.1016/j.jinorgbio.2020.111173
DOI: 10.5517/ccdc.csd.cc24fdxx
title: CCDC 1979099: Experimental Crystal Structure Determination

description: Related Article: Shaozhan Shi, Shui Yu, Lixia Quan, Majid Mansoor, Zilu Chen, Huancheng Hu, Dongcheng Liu, Yuning Liang, Fupei Liang|2020|J.Inorg.Biochem.|210|111173|doi:10.1016/j.jinorgbio.2020.111173
DOI: 10.5517/ccdc.csd.cc24fdyy
title: CCDC 1979100: Experimental Crystal Structure Determination

description: Related Article: Shaozhan Shi, Shui Yu, Lixia Quan, Majid Mansoor, Zilu Chen, Huancheng Hu, Dongcheng Liu, Yuning Liang, Fupei Liang|2020|J.Inorg.Biochem.|210|111173|doi:10.1016/j.jinorgbio.2020.111173
DOI: 10.5517/ccdc.csd.cc24fdzz
title: CCDC 1979101: Experimental Crystal Structure Determination

description: Related Article: Shaozhan Shi, Shui Yu, Lixia Quan, Majid Mansoor, Zilu Chen, Huancheng Hu, Dongcheng Liu, Yuning Liang, Fupei Liang|2020|J.Inorg.Biochem.|210|111173|doi:10.1016/j.jinorgbio.2020.111173
DOI: 10.5517/ccdc.csd.cc24ff01
title: CCDC 1979102: Experimental Crystal Structure Determination

description: Related Article: Shaozhan Shi, Shui Yu, Lixia Quan, Majid Mansoor, Zilu Chen, Huancheng Hu, Dongcheng Liu, Yuning Liang, Fupei Liang|2020|J.Inorg.Biochem.|210|111173|doi:10.1016/j.jinorgbio.2020.111173
DOI: 10.5517/ccdc.csd.cc24fgjl
title: CCDC 1979149: Experimental Crystal Structure Determination

description: Related Article: Chang-Sheng Wang,  Sabrina Di Monaco,  Anh Ngoc Thai,  Md. Shafiqur Rahman,  Benjamin Piaoxiang Pang,  Chen Wang,  Naohiko Yoshikai|2020|J.Am.Chem.Soc.|142|12878|doi:10.1021/jacs.0c06412
DOI: 10.5517/ccdc.csd.cc24kbnq
title: CCDC 1982873: Experimental Crystal Structure Determination

description: Related Article: Vitalii Yu. Kotov, Petr A. Buikin, Nikolay P. Simonenko, Andrey B. Ilyukhin|2020|J.Mol.Struct.|1221|128807|doi:10.1016/j.molstruc.2020.128807
DOI: 10.5517/ccdc.csd.cc24kbpr
title: CCDC 1982874: Experimental Crystal Structure Determination

description: Related Article: Vitalii Yu. Kotov, Petr A. Buikin, Nikolay P. Simonenko, Andrey B. Ilyukhin|2020|J.Mol.Struct.|1221|128807|doi:10.1016/j.molstruc.2020.128807
DOI: 10.5517/ccdc.csd.cc24kbqs
title: CCDC 1982875: Experimental Crystal Structure Determination

description: Related Article: Vitalii Yu. Kotov, Petr A. Buikin, Nikolay P. Simonenko, Andrey B. Ilyukhin|2020|J.Mol.Struct.|1221|128807|doi:10.1016/j.molstruc.2020.128807
DOI: 10.5517/ccdc.csd.cc24kbrt
title: CCDC 1982876: Experimental Crystal Structure Determination

description: Related Article: Vitalii Yu. Kotov, Petr A. Buikin, Nikolay P. Simonenko, Andrey B. Ilyukhin|2020|J.Mol.Struct.|1221|128807|doi:10.1016/j.molstruc.2020.128807
DOI: 10.5517/ccdc.csd.cc24kbsv
title: CCDC 1982877: Experimental Crystal Structure Determination

description: Related Article: Vitalii Yu. Kotov, Petr A. Buikin, Nikolay P. Simonenko, Andrey B. Ilyukhin|2020|J.Mol.Struct.|1221|128807|doi:10.1016/j.molstruc.2020.128807
DOI: 10.5517/ccdc.csd.cc24mdck
title: CCDC 1984848: Experimental Crystal Structure Determination

description: Related Article: Richard Y. Kong,  Mark R. Crimmin|2020|J.Am.Chem.Soc.|142|11967|doi:10.1021/jacs.0c03383
DOI: 10.5281/zenodo.3979480
title: 200 kHz pre-processed echosounder data collected on the Antarctic Circumnavigation Expedition during the austral summer of 2016/2017.

description: <strong>Dataset abstract </strong> These data consist of pre-processed echosounder observations in the Southern Ocean collected during the Antarctic Circumnavigation Expedition (ACE; Leg2-Leg3) using an EK60 GPT operating at 200 kHz. The instrument was calibrated at South Georgia during the expedition (Leg 3) and corrections were applied prior to calculation of the volume backscattering strength (Sv). The signal-to-noise ratio (SNR) was analysed and was deemed very poor at depths greater than 100 m. Therefore, only data collected between the transducer depth (8.4 m) and 100 m were archived. <strong>Dataset contents</strong> ACE-DYYYYMMDD-THHMMSS.csv, data files, comma-separated values data_file_header.txt, metadata, text README.txt, metadata, text <strong>Dataset license</strong> This 200 kHz pre-processed echosounder data collected on ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/
description: The Antarctic Circumnavigation Expedition was made possible by funding from the Swiss Polar Institute and Ferring Pharmaceuticals.
description: {"references": ["Proud, R., Le Guen, C., Fernandes, P., Everson, I., Bernasconi, M., Lawrence, J. and Brierley, A. (2020). 200 kHz raw echosounder data collected on the Antarctic Circumnavigation Expedition during the austral summer of 2016/2017. (Version 1.0) [Data set]. Zenodo. DOI: 10.5281/zenodo.", "https://www.echoview.com/products-services/news/important-echoview-8-update-for-simrad-ek80-users", "Proud, R., Le Guen, C., Fernandes, P., Everson, I., Bernasconi, M., Lawrence, J. and Brierley, A. (2020). 200 kHz raw echosounder data collected on the Antarctic Circumnavigation Expedition during the austral summer of 2016/2017. (Version 1.0) [Data set]. Zenodo. DOI: 10.5281/zenodo.0"]}
DOI: 10.5281/zenodo.3979479
title: 200 kHz pre-processed echosounder data collected on the Antarctic Circumnavigation Expedition during the austral summer of 2016/2017.

description: <strong>Dataset abstract </strong> These data consist of pre-processed echosounder observations in the Southern Ocean collected during the Antarctic Circumnavigation Expedition (ACE; Leg2-Leg3) using an EK60 GPT operating at 200 kHz. The instrument was calibrated at South Georgia during the expedition (Leg 3) and corrections were applied prior to calculation of the volume backscattering strength (Sv). The signal-to-noise ratio (SNR) was analysed and was deemed very poor at depths greater than 100 m. Therefore, only data collected between the transducer depth (8.4 m) and 100 m were archived. <strong>Dataset contents</strong> ACE-DYYYYMMDD-THHMMSS.csv, data files, comma-separated values data_file_header.txt, metadata, text README.txt, metadata, text <strong>Dataset license</strong> This 200 kHz pre-processed echosounder data collected on ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/
description: The Antarctic Circumnavigation Expedition was made possible by funding from the Swiss Polar Institute and Ferring Pharmaceuticals.
description: {"references": ["Proud, R., Le Guen, C., Fernandes, P., Everson, I., Bernasconi, M., Lawrence, J. and Brierley, A. (2020). 200 kHz raw echosounder data collected on the Antarctic Circumnavigation Expedition during the austral summer of 2016/2017. (Version 1.0) [Data set]. Zenodo. DOI: 10.5281/zenodo.", "https://www.echoview.com/products-services/news/important-echoview-8-update-for-simrad-ek80-users", "Proud, R., Le Guen, C., Fernandes, P., Everson, I., Bernasconi, M., Lawrence, J. and Brierley, A. (2020). 200 kHz raw echosounder data collected on the Antarctic Circumnavigation Expedition during the austral summer of 2016/2017. (Version 1.0) [Data set]. Zenodo. DOI: 10.5281/zenodo.0"]}
DOI: 10.5281/zenodo.3981252
title: Ultra-wideband SAR Tomography on asteroids : FDBP and Compressive Sensing datasets

description: Our knowledge of the internal structure of asteroids is currently indirect and relies on inferences from remote sensing observations of surfaces. However, it is fundamental for understanding small bodies’ history and for planetary defense missions. Radar observation of asteroids is the most mature technique available to characterize their inner structure, and Synthetic Aperture Radar Tomography (TomoSAR) allows 3D imaging by extending the synthetic aperture principle in the elevation direction. However, as the geometry of observation of small asteroids is complex, and TomoSAR studies have always been performed in the Earth observation geometry, TomoSAR results in a small body geometry must be simulated to assess the methods’ performances. Different tomography algorithms can be adopted, depending on the characteristics of the problem. While the Frequency Domain Back Projection (FDBP) is based on the correction of the Fourier transform of the received signal by an <em>ad-hoc</em> function built from the geometry of study, it can only retrieve the true position of the scatterers when applied along with ray-tracing methods, which are unreliable in the case of rough asteroid surfaces. Meanwhile, the Compressive Sensing (CS) is based on the compressive sampling theory, which relies on the hypothesis that few scatterers lie in the same direction from the subsurface. The CS can be used to retrieve the position of the scatterers, but its application in the small body geometry is questioned. Thus, both performances of the FDBP and the CS in a small body geometry are demonstrated, and the quality of the reconstruction is analyzed.
DOI: 10.5281/zenodo.3981251
title: Ultra-wideband SAR Tomography on asteroids : FDBP and Compressive Sensing datasets

description: Our knowledge of the internal structure of asteroids is currently indirect and relies on inferences from remote sensing observations of surfaces. However, it is fundamental for understanding small bodies’ history and for planetary defense missions. Radar observation of asteroids is the most mature technique available to characterize their inner structure, and Synthetic Aperture Radar Tomography (TomoSAR) allows 3D imaging by extending the synthetic aperture principle in the elevation direction. However, as the geometry of observation of small asteroids is complex, and TomoSAR studies have always been performed in the Earth observation geometry, TomoSAR results in a small body geometry must be simulated to assess the methods’ performances. Different tomography algorithms can be adopted, depending on the characteristics of the problem. While the Frequency Domain Back Projection (FDBP) is based on the correction of the Fourier transform of the received signal by an <em>ad-hoc</em> function built from the geometry of study, it can only retrieve the true position of the scatterers when applied along with ray-tracing methods, which are unreliable in the case of rough asteroid surfaces. Meanwhile, the Compressive Sensing (CS) is based on the compressive sampling theory, which relies on the hypothesis that few scatterers lie in the same direction from the subsurface. The CS can be used to retrieve the position of the scatterers, but its application in the small body geometry is questioned. Thus, both performances of the FDBP and the CS in a small body geometry are demonstrated, and the quality of the reconstruction is analyzed.
DOI: 10.5281/zenodo.3981210
title: Pictogramas ARASAAC Color, Part 13 of 16

description: Black and white pictograms created by Sergio Palao (http://www.palao.es) for ARASAAC (http://www.arasac.org).
DOI: 10.5281/zenodo.3981209
title: Pictogramas ARASAAC Color, Part 13 of 16

description: Black and white pictograms created by Sergio Palao (http://www.palao.es) for ARASAAC (http://www.arasac.org).
DOI: 10.6073/pasta/d7c6e94ab80ed2ca18f29935877f91e4
title: Biogeochemical data collected from Northeast Shark River Slough, Everglades National Park, Florida from September 2006 to present

description: This project was established in 2006 to document the pattern of abundance of key ecological indicators (e.g., surface water, soil, floc, periphyton and sawgrass) across the NESRS landscape (Gaiser et al. 2009). A total of 30 sites were established and monitored in 2006, 2007 and 2008 .After the completion of 1-mile bridge in 2012, additional 10 new sites were established to observe the ecological impact of 1-mile bridge ( Known as Bridge & Census sites). In 2015, additional 40 sites were established along eight transects (T1-T8, known as near canal sites) in ENP marshes starting at, and roughly perpendicular to the L-29 canal. The purpose of these sites was to monitor the potential effects of Modified Water Deliveries (MWD) operations on changing nutrient concentrations and ratios in key ecological compartments due to increased downstream discharges from the L-29 canal beneath the 1-mile and 2.6-mile bridges and culverts along Tamiami Trail.
DOI: 10.5281/zenodo.3975035
title: Polygenic modelling of treatment effect heterogeneity

description: Xu, ZM, Burgess, S. Polygenic modelling of treatment effect heterogeneity. <em>Genetic Epidemiology</em>. 2020; 1– 12. https://doi.org/10.1002/gepi.22347 File contains: 1. Summary statistics of genome-wide interaction study (between moderating variants and HMGCR pharmacomimetic score) 2. Random forest of interaction tree (RFIT) objects. See README for detail
DOI: 10.5281/zenodo.3975034
title: Polygenic modelling of treatment effect heterogeneity

description: Xu, ZM, Burgess, S. Polygenic modelling of treatment effect heterogeneity. <em>Genetic Epidemiology</em>. 2020; 1– 12. https://doi.org/10.1002/gepi.22347 File contains: 1. Summary statistics of genome-wide interaction study (between moderating variants and HMGCR pharmacomimetic score) 2. Random forest of interaction tree (RFIT) objects. See README for detail
DOI: 10.15468/y7ks3k
title: Anewspecies of the cricket genus, Cacoplistes from Rajasthan, India (Orthoptera: Phalangopsidae: Cachoplistinae: Cachoplistini)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Meena, Ashok Kumar, Swaminathan, Rajamai, Nagar, Rajendra (2020): Anewspecies of the cricket genus, Cacoplistes from Rajasthan, India (Orthoptera: Phalangopsidae: Cachoplistinae: Cachoplistini). Zootaxa 4755 (3): 598-599, DOI: https://doi.org/10.11646/zootaxa.4755.3.12
DOI: 10.15468/yvtf3g
title: A new species of Setostylus Matile and new records of Setostylus bellulus (Williston) (Diptera: Keroplatidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Huerta, Heron, Fitzgerald, Scott J. (2020): A new species of Setostylus Matile and new records of Setostylus bellulus (Williston) (Diptera: Keroplatidae). Zootaxa 4755 (3): 600, DOI: https://doi.org/10.11646/zootaxa.4755.3.13