Find research datasets worth reusing

Ab initio molecular dynamics trajectories of liquid water at the interface with MoS2 sheets

Ab initio molecular dynamics trajectories of water confined between MoS2 sheets for different confinement widths and system sizes. This repository contains data supporting the findings of the paper:  G. Tocci, M. Bilichenko, L. Joly, M. Iannuzzi, Ab initio nanofluidics: disentangling the role of the energy landscape and of density correlations on liquid/solid friction, Nanoscale, 12, 10994-11000 (2020). DOI: 10.1039/D0NR02511A.

Do Go Chasing Waterfalls: Enoyl Reductase (FabI) in Complex with Inhibitors Stabilizes the Tetrameric Structure and Opens Water Channels - trajectories employed in Markov State Models and water analyses

The following trajectories were employed in the generation of MSM models and water analyses: SaFabI_60us_align.zip EcFabI_60us_align.zip waters_SaFabI.tar.gz waters_EcFabI.tar.gz

Dominant Rural Technological Trajectories (TTs) dataset at municipality level of the Brazilian Legal Amazon (BLA)

This dataset contains the dominant technological trajectories (TTs) of the Brazilian Legal Amazon (BLA) municipalities for the years of 1995, 2006 and 2017. The dominant trajectory is the one, among the six identified by Costa (2021), that is economically most important in the municipality. The relative share of the Gross Value of Rural Production of the trajectory in the total Gross Value of Rural Production in the municipality was taken as a proxy of economic importance. From the tabulation of the datasets in Costa (2022), the dominant technological trajectory was identified, it means, considering the methodology used, which of the six TTs was responsible for over 50% of the municipal Gross Value of Rural Production. The dominant TTs were calculated using the official municipal grid for the year the agricultural census was carried out. The dataset is organized as a .csv table, for each year (1995, 2006 and 2017), with a geographic key for each municipality (6-digit municipality code, 2-digit state code), that can be easily linked with municipality available shapefiles and other datasets.  References: Costa, F. A. Structural diversity and change in rural Amazonia: a comparative assessment of the technological trajectories based on agricultural censuses (1995, 2006 and 2017). Nova econ. 31 (02), May-Aug 2021, doi:10.1590/0103-6351/6373. Costa, F. A, (2022). Database of Rural Technological Trajectories of the Legal Amazon delimited by the Method of Differentiation and Structural Signification of Rural Production (M-DASTRU). Zenodo. DOI: 10.5281/zenodo.7035753

Dominant Rural Technological Trajectories (TTs) dataset at municipality level of the Amazon Biome

This dataset contains the dominant technological trajectories (TTs) of the Amazon Biome municipalities for the years of 1995, 2006 and 2017. The dominant trajectory is the one, among the six identified by Costa (2021), that is economically most important in the municipality. The relative share of the Gross Value of Rural Production of the trajectory in the total Gross Value of Rural Production in the municipality was taken as a proxy of economic importance. From the tabulation of the datasets in Costa (2021), the dominant technological trajectory was identified, it means, considering the methodology used, which of the six TTs was responsible for over 50% of the municipal Gross Value of Rural Production. The dominant TTs were calculated using the official municipal grid for the year the agricultural census was carried out. The dataset is organized as a .csv table, for each year (1995, 2006 and 2017), with a geographic key for each municipality (6-digit municipality code, 2-digit state code), that can be easily linked with municipality available shapefiles and other datasets.  References: Costa, F. A. Structural diversity and change in rural Amazonia: a comparative assessment of the technological trajectories based on agricultural censuses (1995, 2006 and 2017). Nova econ. 31 (02), May-Aug 2021, doi:10.1590/0103-6351/6373.

opencc-by-4.0Feb 2022View details →

A computational method for predicting the most likely evolutionary trajectories in the stepwise accumulation of resistance mutations

Supporting information dataset for A computational method for predicting the most likely evolutionary trajectories in the stepwise accumulation of resistance mutations, including Flex ddG binding free energy predictions, epistasis calculations, pathway probabilities, Rosetta files and structural files.

opencc-by-4.0Sep 2022View details →

Database of Rural Technological Trajectories, their variants and territories featured by peasantries of the Brazilian Northern Region based on Agricultural Censuses and special tabulations for the Economy of Agroforestry Systems (2006 and 2017)

Introduction This database contains the string variables at municipal level that qualifies the techno-productive trajectories (TT) of the Brazilian Northern Region Agrarian Economy, their technological variants (TTV) and territories based on peasantries. The TTs and TTVs were defined and theoretically justified by Costa (2021, p. 217-219). Delimitation of Technological Trajectories, their variants and territories featured by peasantries The TTs are designed by a method that combines differentiation and structural signification of rural production in each territory – hereafter, Method of Differentiation and Structural Signification of Rural Production (M-DESTRU). Structural differentiation (Phase 1) is necessary because production systems activities play different roles, depending on the systems  production modes and their territorial context: cattle ranching, for example, performs very different economic functions when practiced in family structures (peasants) in the municipalities of the Lower Amazonas, in comparison with wage-based farms in Southeast Pará; the roles played by temporary crops in the peasant systems of the Lower Tocantins are also quite different from those that are observed among employers' establishments in the Lower Amazon; and so on. This phase of the methodology qualifies these differences and has its procedures described on pages 440 and 441 of Costa (2021). In phase 2, M-DESTRU verifies how these structurally dissimilar activities, combine with others linked to the practices of the agents of each production mode, conforming convergences that result in distinct patterns. These patterns are semantically associated with TTs or TTPs structures that are in movement, and these structures all together make up for the region's rural economic system. This Phase's procedures are detailed on pages 441 and 442 of the aforementioned work. The codes of variable “Technological Trajectories” in this database are “CamponêsT1” for “Peasant Trajectory.T1” in Costa, 2021; “CamponêsT2” for “Peasant Trajectory.T2”; “CamponêsT3” for “Peasant Trajectory.T3”; “PatronalT4” for “Employer.T4”; “PatronalT5” for “Employer.T5”; “PatronalT7” for “Employer.T7”. In turn, the procedures to get the technological variants of TTs (TTVs) for census years 2006 and 2017 are described in Costa, 2021, p. 447-451. The codes of variable “Technological Variants” in this database are “IQ” for “CI = Chemical Intensity” in Costa, 2021; “IM” for “MI = Mechanical Intensity”; “IT” for “LI = Labour Intensity”; “IPst” for “PI = Pasture Improvement”; “IReb” for “HI = Herd improvement”; “Crg” for “LoadC=Load Capacity of Pasture”; “SAF-F” for “AFSs-F = AFSs with the presence of forest management”; “SAF-A” for “AFSs-A = Artificially developed AFSs”; “+” after the attribute for “Attribute clearly verified; “–“ for “Attribute clearly absent”; “0” for “an uncertain attribute”. The Brazilian Northern Region encompasses the municipalities of the federative states Acre, Amapá, Amazonas, Mato Grosso, Pará, Rondônia, Roraima and Tocantins. A municipality is codified by the variable “Peasantry” as “ACaboclo_Originário”, meaning a territory of an “original caboclo peasantry (OcP in English or CbO in Portuguese)”, if founded before 1880; “BCaboclo_Forâneo”, meaning a territory of an ”immigrant caboclo peasants (IcP or CbF)”, if founded between 1880 and 1910; “CAgrícola_Forâneo, meaning a territory of a “post-ruber immigrant agricultural peasantry (IpR or FpB)”, if founded  between 1910 and 1960; and “DContemporâneo”, meaning a “recent peasantry (ReP or ReC)”, if founded since 1960. The base data are from the Brazilian Institute of Geography and Statistics (IBGE), from the 2006 and 2017 Agricultural Censuses. The following special cases were handled: <ul> <li>In the Agricultural Census 2017 credit data were not available. However, the Central Bank of Brazil informs for that year total rural credit for family-based and non-family-based agriculture and livestock by municipality.</li> <li>Comparing the production of manioc in the 2006 census with the production of manioc flour in the same year and with the historical production, we arrived at errors in three municipalities in Pará: in Moju a manioc production of 498,907 t is recorded adding the two sets of data (Peasant and Employer), when in fact it is 42,132; in São Miguel do Guamá the figure of 392,784 t is recorded when it actually is 175,941; 204,216 is recorded in Viseu and 106,287 is actual figure. Corrections were made using the proportion manioc/manioc flour prevailing in other municipalities in same microregion.</li> <li>In the census there are the value of the production of manioc and the value of the production of manioc flour. Since we are dealing with the same producer, if we consider in gross value of production or income aggregations both products, we incur double counting. In such cases, the value related to manioc flour was considered.</li> <li>The 2006 census has information on fishing restricted to the monetary income from the sale of fish, as a complementary income variable. The information does not incorporate the value of fish consumed in the establishment. Therefore, it is not a variable equivalent to the GVP of all other products considered. In turn, the 2017 census provides data on fish production as part of livestock (the gross value of fish production in captivity, which makes up the gross value of livestock production) but does not maintain the fish sales variable from the previous census. This income is contained in the variable “other producer income”, in which, none of the other possibilities listed (esgargot, etc.) are adhered to T2 (IBGE, Censo Agropecuário de 2017. Rio de Janeiro, IBGE, 2018). Therefore, two things were done to incorporate fisheries: a) for 2006 the GVP of fishery production was considered the variable "fish sale" under the heading "other producer income" divided by 1 minus the self-consumption rate 31% (Costa et al, 2022); b) for 2017, the GVP of fisheries production resulted from the division of the variable “other producer's incomes” by the same denominator of the operation described in “a”.</li> </ul> The dataset is organized as: 1. Data set with variables delimiting TT, TTV and Peasantry 2006_NorthRegion_TechVariants.csv 2017_ NorthRegion_TechVariants.csv. In each table the column names are self-explanatory. 2. Dataset with special tabulation or the agroforestry systems economy represented by Peasant Trajectory.T2     Gross Value of Production     Table1_NorthRegion_T2_GVP.csv      Table 1a – Gross Value of Productios (GVP) by products of AFSs-F and peasantry 2006 and 2017     Table 1b – Gross Value of Productios (GVP) by products of AFSs-A and peasantry, 2006 and 201     Table 1c – Gross Value of Productios (GVP) by products of T2, technological variant, and peasantry, 2006 and 2017       Real Product      Real Product” (RP): For each year (i), the vector of produced quantities (Qi) multiplied by a vector of fixed prices (P1): variation of RP is explained exclusively by the variation of Q.        Table2_NorthRegion_T2_RealProduct.csv       Table 2a – T2 Production by technological variant and peasantry, 2006       Table 2b – T2 Production Value (=Real Product) by technological variant, and peasantry, 2006 in R$ 1,000 currents       Table 2c – T2 Implicit prices by technological variant, and peasantry, 2006, R$ 1.000 currents (each cel in Table 2b divided by corresponding cel in Table 2a)       Table 2d – T2 Production by technological variant, and peasantry, 2017       Table 2e – T2 Real Product1 by technological variant, and peasantry, 2017 in R$ 1,000 from 2006 (each cel in Table 2c multiplied by corresponding cel in Table 2d)        Key variables       Table3_NorthRegion_T2_KeyVariables.csv        Table 3 – Key variables of T2 economy by peasantry, 2006 and 2017 Reference: Costa FA. 2021. Structural diversity and change in rural Amazonia: A comparative assessment of the technological trajectories based on agricultural censuses (1995, 2006 and 2017). Nova Economia 31(2). COSTA, F. A., FEIJÃO,, L. G., ALMEIDA, I. C., NOGUEIRA, K. N. S., AMERICO, M. C. (2022). Database of a Riverine Economy in Mocajuba, Low Tocantins, Pará, Amazonia, Brazil [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7121336

opencc-by-4.0Oct 2022View details →

To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features - Dataset

This repository contains the reproduction steps and intermediate artifacts corresponding to the paper 'To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features'. During the submission process, this repository is anonymized to our best ability.  The file 'README' contains the description of which file contains what data, and how they correspond to different parts of the paper.

MD simulation trajectory of a POPC/POPS (4:1) bilayer with 715mM CaCl2, Berger force field for lipids, scaled charges for Ca2+ and Cl-

MD simulation trajectory of a POPC/POPS (4:1) bilayer with 715 mM CaCl2 (104 POPC, 24 POPS, 26 POPS, 4306 WAT, 72 Ca2+, 112 Cl-). Additional Ca2+ cations added to neutralize the negative charge of POPS (leading to total Ca2+ concentration of 919 mM). Berger force field for lipids, scaled charges employed for calcium and chloride ions. Gromacs 4.5.5, T=310K, 300 ns trajectories were calculated with the last 100 ns stored here. Used in (see therein also a detailed description of ion scaling): A. Melcrova, S. Pokorna, S. Pullanchery, M. Kohagen, P. Jurkiewicz, M. Hof, P. Jungwirth, P. S. Cremer, L. Cwiklik, The complex nature of calcium cation interactions with phospholipid bilayers Scientific Reports 2016, 6, 38035. DOI: 10.1038/srep38035

MD simulation trajectory of a POPC bilayer with 716mM CaCl2, Berger force field for lipids, scaled charges for Ca2+ and Cl-

MD simulation trajectory of a POPC bilayer with 716 mM CaCl2 (128 POPC, 26 POPS, 4308 WAT, 56 Ca2+, 112 Cl-). Berger force field for lipids, scaled charges employed for calcium and chloride ions. Gromacs 4.5.5, T=310K, 200 ns trajectories were calculated with the last 100 ns stored here. Used in (see therein also a detailed description of ion scaling): A. Melcrova, S. Pokorna, S. Pullanchery, M. Kohagen, P. Jurkiewicz, M. Hof, P. Jungwirth, P. S. Cremer, L. Cwiklik, The complex nature of calcium cation interactions with phospholipid bilayers Scientific Reports 2016, 6, 38035. DOI: 10.1038/srep38035

MD simulation trajectory of a POPC/POPS (4:1) bilayer with 102mM CaCl2, Berger force field for lipids, scaled charges for Ca2+ and Cl-

MD simulation trajectory of a POPC/POPS (4:1) bilayer with 102 mM CaCl2 (104 POPC, 24 POPS, 26 POPS, 4306 WAT, 24 Ca2+, 16 Cl-). Additional Ca2+ cations added to neutralize the negative charge of POPS (leading to total Ca2+ concentration of 306 mM). Berger force field for lipids, scaled charges employed for calcium and chloride ions. Gromacs 4.5.5, T=310K, 300 ns trajectories were calculated with the last 100 ns stored here. Used in (see therein also a detailed description of ion scaling): A. Melcrova, S. Pokorna, S. Pullanchery, M. Kohagen, P. Jurkiewicz, M. Hof, P. Jungwirth, P. S. Cremer, L. Cwiklik, The complex nature of calcium cation interactions with phospholipid bilayers Scientific Reports 2016, 6, 38035. DOI: 10.1038/srep38035

MD simulation trajectory of a POPC bilayer with 100mM CaCl2, Berger force field for lipids, scaled charges for Ca2+ and Cl-

MD simulation trajectory of a POPC bilayer with 100 mM CaCl2 (128 POPC, 26 POPS, 4452 WAT, 8 Ca2+, 16 Cl-). Berger force field for lipids, scaled charges employed for calcium and chloride ions. Gromacs 4.5.5, T=310K, 200 ns trajectories were calculated with the last 100 ns stored here). Used in (see therein also a detailed description of ion scaling): A. Melcrova, S. Pokorna, S. Pullanchery, M. Kohagen, P. Jurkiewicz, M. Hof, P. Jungwirth, P. S. Cremer, L. Cwiklik, The complex nature of calcium cation interactions with phospholipid bilayers Scientific Reports 2016, 6, 38035. DOI: 10.1038/srep38035

opencc-zeroApr 2024View details →

Reinforcing Tunnel Network Exploration in Proteins using Gaussian Accelerated Molecular Dynamics (parameters, trajectories)

<ul> <li>00_LinB-Wt.tar.gz - LinB-Wt simulation files:</li> </ul>     1.cMD(Classical MD simulation):              1. Stripped parameter file *.parm7.         2. Simulation file after removing ions and water and merging last 5us of production run in amber *.nc format.                      2.GaMD(Gaussian Accelerated MD simulation):                1. Stripped parameter file *.parm7.         2. Simulation file after removing ions and water and merging last 5us of production run in amber *.nc format. <ul> <li>01_LinB-Open.tar.gz - LinB Open mutant simulation files:</li> </ul>     1.cMD(Classical MD simulation):              1. Stripped parameter file *.parm7.          2. Simulation file after removing ions and water and merging last 5us of production run in amber *.nc format.                      2.GaMD(Gaussian Accelerated MD simulation):          1. Stripped parameter file *.parm7.         2. Simulation file after removing ions and water and merging last 5us of production run in amber *.nc format. <ul> <li>02_LinB-Closed.tar.gz - LinB Closed mutant simulation files:</li> </ul>     1.cMD(Classical MD simulation):         1. Stripped parameter file *.parm7.         2. Simulation file after removing ions and water and merging last 5us of production run in amber *.nc format.                      2.GaMD(Gaussian Accelerated MD simulation):          1. Stripped parameter file *.parm7.         2. Simulation file after removing ions and water and merging last 5us of production run in amber *.nc format.

opencc-by-4.0Apr 2024View details →

Sulfate anomaly during CAFE-EU/BLUESKY 10 days LAGRANTO back trajectories

Short description The dataset contains trajectories along one segment of the flight path during research flight 01 (RF01) during the CAFE-EU/BLUESKY mission. In this segment we observed a particulate sulfate anomaly and are interested in the air mass origin. Therefore, we built a cross structure to sample in total 231 trajectories for each release point. The detailed method and analysis is published in the corresponding and related work.   Funding This project has been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – TRR 301 – Project-ID 428312742, TPChange:  The Tropopause Region in a Changing Atmosphere (<a href="https://tpchange.de/">https://tpchange.de/</a>).

opencc-by-4.0Apr 2024View details →

Dataset of: "The Relativity of Reaching: Motion of the touched surface alters the trajectory of hand movements"

The repository contains the data of the paper: The Relativity of Reaching: Motion of the touched surface alters the trajectory of hand movementsAuthors: Colleen P. Ryan, Simone Ciotti, Priscilla Balestrucci, Antonio Bicchi, Francesco Lacquaniti, Matteo Bianchi, Alessandro Moscatelli

opencc-by-4.0Apr 2024View details →

Molcular Dynamics Trajectories for GPR156 PG No Cholesterol

Note the cholesterol between the dimers were not modelled in these trajectories. Obsolete.   This is not the Molecular Dynamics Data for 10.1038/s41594-024-01224-7 for publication at Shin, J., Park, J., Jeong, J. et al. Constitutive activation mechanism of a class C GPCR. Nat Struct Mol Biol (2024). https://doi.org/10.1038/s41594-024-01224-7 This folder contains the PDB format file ("Topology") and the XTC format file (Trajectories). The timestep in this strided trajectory is 0.5 ns per frame. Periodic boundary condition (pbc) can be restored using VMD's standard pbc commands. But please cite us if you still find this data useful!

opencc-by-4.0May 2024View details →

Trajectories of backtracked passive particles for: "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea"

This collection hosts the trajectories of bactracked passive particles using Ocean Parcels v2.0 (The Parcels v2.0 Lagrangian framework: new field interpolation schemes. Delandmeter, P and E van Sebille (2019), Geoscientific Model Development, 12, 3571–3584) and ocean surface velocity fields from the output of: "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea".  trajectories_2009.tar: trajectories for particles released between 2009-01-01 and 2009-12-31 trajectories_2010.tar: trajectories for particles released between 2010-01-01 and 2010-12-31 (as shown in "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea") trajectories_2011.tar: trajectories for particles released between 2011-01-01 and 2011-12-31 release_sites.csv: release sites for each release date. ocean_parcels_backtrack_VIB_carib12.py : python script to run ocean parcels to generate the trajectories published here.

opencc-by-4.0Jan 2024View details →

DFT-based Monte Carlo Trajectories for Surface Segregation of Disordered FCC AuCuPd Alloys

A zip file containing 600 subfolders named as "mc_run_$idx"". Each subfolder contains an "analysis.json" and "run_state.json" containing an analysis of the surface segregation output and describing the simulation (the composition of the bulk slab, whether the simulation encountered any errors, etc). Optionally also includes a "job.out" with job logs.

opencc-by-4.0Jan 2024View details →

DFT-based Monte Carlo Trajectories for Surface Segregation of Disordered FCC AgAuCu Alloys

A zip file containing 600 subfolders named as "mc_run_$idx". Each subfolder contains an "analysis.json" and "run_state.json" containing an analysis of the surface segregation output and describing the simulation (the composition of the bulk slab, whether the simulation encountered any errors, etc). Optionally also includes a "job.out" with job logs.

opencc-by-4.0May 2024View details →

Tracked trajectories Karlodinium armiger

Datasets containing the tracked trajectories for each experimental replicate with Karlodinium armiger analyzed in the article: The distinctive chemotactic responses of three marine herbivore protists to DMSP and related compounds.  Nomenclature: K + _ + 1 letter identifying the compound  + concentration in uM+ _ + experimental replicate number  for example: K_D20_R1 stands for "Karlodinium armiger, DMSP, 20 uM, third replicate" The compounds are identified with:  D --> DMSP, M--> DMS, A --> Acrylate The datasets are saved as Pandas dataframe and can be opened with the library Pickle