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86 results for “production rate”
Processed Net N2 Flux and Nitrous Oxide Production Rates from a mesocosm experiment, North River, MA, 2022
The data documented here show nitrogen cycling rates (net N2 flux and net N2O flux) from a tidal, freshwater wetland under two stressors in isolation and in combination over two different disturbance regimes. We used intact core mesocosms to examine how nitrogen cycling changed in response to increased temperature and salinity under pulse and press disturbances. We found that net N2 flux rates, defined as the balance between nitrogen fixation and denitrification did not directionally change in response to stressor pulse or press. Instead, it became more variable under both disturbance regimes. Nitrous oxide production rates, however, decreased and became more stable over time in the press scenario, but remained highly variable in the pulse scenario. These findings provide valuable knowledge on the functional potential of the nitrogen cycling microbial communities in tidal, freshwater wetlands when facing future climate variability.
Gas exchange velocities (k600), gas exchange rates (K600), and hydraulic geometries for streams and rivers derived from the NEON Reaeration field and lab collection data product (DP1.20190.001)
This dataset contains estimates of gas exchange velocity, gas exchange rate, and hydraulic parameters for streams calculated from tracer-gas experiments and conservative tracer injections collected by the National Ecological Observatory Network (NEON). All input data were collected by NEON and is available on the NEON data portal at https://data.neonscience.org. Specifically, the NEON Reaeration field and lab collection data product (DP1.20190.001) was used to calculate these estimates. Gas exchange was estimated in two ways: first, following an unpooled frequentist approach and second, following a partially pooled Bayesian approach. In addition, a salt-correction was applied to gas exchange estimates for sites where it was possible and necessary. All estimates of gas exchange are included in the file gasExchange_ds.csv. A recommended selection of these estimates is included in the dataset (best_k600_mPerDay and best_K600_mPerDay). The stanfit objects used for the partially pooled Bayesian approach are also included as site-specific model objects for gas exchange velocities and rates. In addition, water velocity was calculated from conservative tracer injections, and mean water depth was calculated from these water velocity estimates and measurements of wetted width and water discharge. All hydraulic parameters are included in the file hydraulics_ds.csv. All processing code is available in the reaRates R package. NEON is sponsored by the National Science Foundation (NSF) and operated under cooperative agreement by Battelle. This material is based in part upon work supported by NSF through the NEON Program.
Periphyton Net Primary Productivity and Respiration Rates from the Taylor Slough, just outside Everglades National Park (FCE), South Florida from December 1998 to December 2004
Periphyton metabolism is being measured at TS/Ph1b, TS/Ph2, TS/Ph3, TS/Ph4, and TS/Ph5 every 6-8 weeks during the wet season. We quantify metabolic rates of periphyton assemblages using standard oxygen change techniques in 300mL light and dark BOD bottles in triplicate. Using YSI dissolved oxygen probes and meters, we measure dissolved oxygen change as the difference of initial and final oxygen concentrations during a two hour incubation period. We calculate net primary productivity and respiration rates in units of oxygen and carbon, then normalize to the organic content (ash free dry weight) of the incubated periphyton.
Periphyton Net Primary Productivity and Respiration Rates from the Taylor Slough, just outside Everglades National Park, South Florida (FCE) from December 1998 to August 2002
Once per year, at TS/Ph-4 and TS/Ph-5 we incubate periphyton from each site in water from each site in a complete factorial design. We quantify metabolic rates of periphyton assemblages using standard oxygen change techniques in 300mL light and dark BOD bottles in triplicate. Using YSI dissolved oxygen probes and meters, we measure dissolved oxygen change as the difference of initial and final oxygen concentrations over a two hour incubation. We calculate net primary productivity and respiration rates in units of oxygen and carbon, then normalize to the organic content (ash free dry weight) of the incubated periphyton.
Thymidine uptake rates for estimating bacterial production in lakes, McMurdo Dry Valleys, Antarctica (1993-2023, ongoing)
An important part of the McMurdo Long Term Ecological Research (LTER) is monitoring of spatial and temporal patterns, and processes that control bacterial production in perennial ice-covered lakes. This data set quantifies thymidine (TdR) uptake by bacteria, which can be used to estimate bacterial production.
Seawater isoprene loss and production rates across contrasting oceanic regions
<p><strong>Measured biological variables and isoprene process rate constants across contrasting regions of the global ocean. </strong>SST: sea surface temperature;<strong> </strong>SSS: sea surface salinity; Z<sub>ML</sub>: mixed layer depth; U<sub>10</sub> 24h: wind speed at 10 m above sea surface, averaged over 24 hours; chl<em>a</em>: chlorophyll-<em>a</em> concentration; BA: bacterial abundance; k<sub>loss</sub>: rate constant of isoprene loss in incubations (microbial degradation + chemical oxidation); k<sub>vent</sub>: rate constant of isoprene ventilation to the atmosphere; k<sub>mix</sub>: rate constant of isoprene vertical mixing by turbulent diffusion at the bottom of the mixed layer (negative means import into the surface mixed layer); total τ: turnover time due to all sinks; k<sub>prod</sub>: rate constant of isoprene production, assuming 24-h steady state for the isoprene concentration; sp. prod. rate: chl<em>a</em>-normalized daily rate of isoprene production.</p> <p><strong>Results of the coastal seawater dark incubations for isoprene loss kinetics. </strong>SST: lab-incubation temperature (within ±0.5ºC of the in-situ temperature); chl<em>a</em>: chlorophyll-<em>a</em> concentration; isoprene concentration; std err: standard error of duplicate isoprene concentration measurements. The experiments were conducted with water from the Blanes Bay Microbial Observatory (coastal NW Mediterranean) and the coral reef lagoon of Moorea (French Polynesia).</p> <p><strong>Results of the coastal seawater dark incubations for isoprene oxidation assays. </strong>SST: in-situ and incubation temperature; chl<em>a</em>] chlorophyll-<em>a</em> concentration; isoprene concentration. </p>
Increased Central European forest mortality explained by higher harvest rates driven by enhanced productivity
<p># Increased Central European forest mortality explained by higher harvest rates driven by enhanced productivity</p> <p>## Author<br> Marieke Scheel, Lund University, Sweden, marieke.scheel@gmail.com</p> <p>## Description<br> Data underlying analysis in:<br> Marieke Scheel, Mats Lindeskog, Benjamin Smith, Susanne Suvanto, Thomas A. M. Pugh<br> Increased Central European forest mortality explained by higher harvest rates driven by enhanced productivity<br> Scripts underlying analysis:<br> https://github.com/mariekesche/harvest_driven_canopy_mortality</p> <p>Folder: harvest_checks<br> - NFI_Germany.txt, National Forest Index data from Germany as difference between inventories in 200-2003 and 2011-2013, values are given as fraction, n: number of NFI plots in a grid cell, HARVEST_ALL: clear-cut harvest, HARVEST_PARTIAL: thinning harvest, NATDEAD: natural dead (not harvested)</p> <p>Folder: manag_climfix (S_man,clim)<br> - cflux_forest_rel.txt, Net Primary Production (NPP) values of forests in kg [C]/ m^2 year (column 4)<br> - crownloss.txt, m^2 of crown/m^2 of ground lost per year<br> - diam_crownarea.txt, total m^2 of crown/m^2 of ground per year split into DBH classes</p> <p>Folder: manag_co2fix (S_man,CO2)<br> - cflux_forest_rel.txt, Net Primary Production (NPP) values of forests in kg [C]/ m^2 year (column 4)<br> - crownloss.txt, m^2 of crown/m^2 of ground lost per year<br> - diam_crownarea.txt, total m^2 of crown/m^2 of ground per year split into DBH classes</p> <p>Folder: manag_ndepfix (S_man,N)<br> - cflux_forest_rel.txt, Net Primary Production (NPP) values of forests in kg [C]/ m^2 year (column 4)<br> - crownloss.txt, m^2 of crown/m^2 of ground lost per year<br> - diam_crownarea.txt, total m^2 of crown/m^2 of ground per year split into DBH classes</p> <p>Folder: manag_nofix (S_man)<br> - cflux_forest_rel.txt, Net Primary Production (NPP) values of forests in kg [C]/ m^2 year (column 4)<br> - closs.txt, biomass loss in kg [C]/m^2 year split into DBH classes<br> - closs_harv.txt, biomass loss due to harvest in kg [C]/m^2 year split into DBH classes<br> - cpool_forest_rel.txt, biomass of forests in kg [C]/m^2 year<br> - crownloss.txt, m^2 of crown/m^2 of ground lost per year<br> - crownloss_age.txt, m^2 of crown/m^2 of ground lost per year due to age<br> - crownloss_dist.txt, m^2 of crown/m^2 of ground lost per year due to disturbance<br> - crownloss_fire.txt, m^2 of crown/m^2 of ground lost per year due to fire disturbance<br> - crownloss_greff.txt, m^2 of crown/m^2 of ground lost per year due to growth efficiency<br> - crownloss_harv.txt, m^2 of crown/m^2 of ground lost per year due to harvest<br> - crownloss_other.txt, m^2 of crown/m^2 of ground lost per year due to other reasons<br> - crownloss_thin.txt, m^2 of crown/m^2 of ground lost per year due to natural thinning<br> - diam_cmass_wood.txt, wooden biomass in kg [C]/m^2 year split into DBH classes<br> - diam_crownarea.txt, total m^2 of crown/m^2 of ground per year split into DBH classes<br> - diam_dens.txt, total number of trees/m^2 year split into DBH classes<br> - stemloss.txt, number of trees/m^2 year lost in respective cells<br> - stemloss_harv.txt, number of trees/m^2 year lost in respective cells due to harvest</p> <p>Folder: manag_nothin (S_nothin)<br> - cflux_forest_rel.txt, Net Primary Production (NPP) values of forests in kg [C]/ m^2 year (column 4)<br> - crownloss.txt, m^2 of crown/m^2 of ground lost per year<br> - diam_cmass_wood.txt, wooden biomass in kg [C]/m^2 year split into DBH classes<br> - diam_crownarea.txt, total m^2 of crown/m^2 of ground per year<br> - lai.txt, leaf area index (LAI) for simulated species and plant functional types (PFTs)</p> <p>Folder: PNV (S_PNV)<br> - cflux.txt, Net Primary Production (NPP) values in kg [C]/ m^2 year (column 4)<br> - crownloss.txt, m^2 of crown/m^2 of ground lost per year<br> - crownloss_age.txt, m^2 of crown/m^2 of ground lost per year due to age<br> - crownloss_dist.txt, m^2 of crown/m^2 of ground lost per year due to disturbance<br> - crownloss_fire.txt, m^2 of crown/m^2 of ground lost per year due to fire disturbance<br> - crownloss_greff.txt, m^2 of crown/m^2 of ground lost per year due to growth efficiency<br> - crownloss_other.txt, m^2 of crown/m^2 of ground lost per year due to other reasons<br> - crownloss_thin.txt, m^2 of crown/m^2 of ground lost per year due to natural thinning<br> - diam_cmass_wood.txt, wooden biomass in kg [C]/m^2 year split into DBH classes<br> - diam_crownarea.txt, total m^2 of crown/m^2 of ground per year split into DBH classes</p> <p>Folder: dependencies<br> - gridlist.txt, coordinates of 0.5°x0.5° grid cells that simulations were run on; longitude, latitude, FAO number, size in m^2<br> - landcover_eu.txt, input file LPJ-GUESS model showing changes from natural to forest (harvest); longitude, latitude, year, natural, forest, barren</p> <p>## Dependencies<br> - canopy mortality rates published in "Senf C Pflugmacher D Zhiqiang Y Sebald J Knorn J Neumann M Hostert P and Seidl R 2018 Canopy mortality has doubled in Europe’s temperate forests over the last three decades Nature Communications 9 4978 10.1038/s41467-018-07539-6"<br> - harvest removal rates published in "Ceccherini G Duveiller G Grassi G Lemoine G Avitabile V Pilli R and Cescatti A 2020<br> Abrupt increase in harvested forest area over Europe after 2015 Nature 583 72-77 10.1038/s41586-020-2438-y"<br> - FAO forest removal area data data retrieved from https://www.fao.org/faostat/en/#data/GF (24.07.2021), modified for overview (1st column: Area Code, 2nd column: Year, 3rd column: Area in 1000 ha)</p>
Gridded products of global river methane concentrations, flux rates and emissions
<p><strong>Information on the products on this repository</strong></p> <p>These data is created using the R scripts with the random forest models and upscaling procedures found in: https://github.com/rocher-ros/RiverMethaneFlux.</p> <p>Raw files to reproduce this product can be found in https://doi.org/10.5281/zenodo.7733604</p> <p>The results of this analysis are published in the article "Global Methane emissions form rivers and streams" (in Nature) (https://doi.org/10.1038/s41586-023-06344-6).</p> <p>Main author is Gerard Rocher-Ros, for which correspondence can be sent to g.rocher.ros@gmail.com</p> <p>Units of the variables in the product are:<br> -River methane concentration: mmol CH4 m-3<br> -River methane diffusive flux rates: mmol CH4 m-2 d-1 (of river area)<br> -River methane diffusive emissions: Mega grams of C-CH4 (for each pixel).</p> <p>The spatial resolution of the product is 0.25 degrees (which corresponds to around 27 km). The files are in WGS84.</p> <p>There are four main products in this folder, packed as geotiff files, and described below.</p> <p>+ The file "river_methane_yearly.tiff" contains three layers:<br> - Yearly average river CH4 concentrations (ch4_conc_avg)<br> - Yearly average river CH4 diffusive flux rates (ch4_flux_avg)<br> - Yearly total river CH4 diffusive emissions (ch4_emissions_year)</p> <p>+ The file "river_methane_concs_monthly.tiff" contains twelve layers, with the modelled river methane concentrations for each month.</p> <p>+ The file "river_methane_flux_monthly.tiff" contains twelve layers, with the modelled river methane flux rates for each month.</p> <p>+ The file "river_methane_emissions_monthly.tiff" contains twelve layers, with the total river methane emissions for each month.</p>
Instantenous rates of ecosystem carbon fluxes: The influence of natural enemies on plant community composition and productivity
The purpose of this experiment is to determine the influences of natural enemies, including plant pathogenic fungi and insect pests, influence plant community composition, productivity, and diversity over time. The experiment is being conducted in an old field that is burned every other year. Within the old field, there are 8 blocks, and within each block there are 6 treatments: foliar fungicide, soil drench fungicide, foliar insecticide, mammal exclosure, the combination of all enemy suppression tactics (pesticides and mammal exclosure), and a nontreated control. The pesticides are applied repeatedly throughout the growing season. Within the plots, community productivity, species composition, percent cover, and pest damage are being quantified over time.
Tabulation and interpolation of NLO neutrino-antineutrino production and scattering rates at MeV temperatures
<p>This record contains data used in the paper "<em>Neutrino-antineutrino production, annihilation, and scattering at MeV temperatures and NLO accuracy</em>" <a href="https://arxiv.org/abs/2412.03958">2412.03958</a>. Please consult the main text for details on the tabulated coefficients and their proper implementations.</p> <p>We provide numerical data and an interpolation routine (c-code) for evaluating double-differential rates, intended to facilitate possible studies of the full kinetic equations for neutrino decoupling in the early universe. These data can also be used to obtain integrated quantities, such as the energy density transfer rates, or neutrino interaction rates (e.g. <a href="https://arxiv.org/abs/2312.07015">2312.07015</a>). The QED corrections to the spectral functions were computed using an adapted version of the public code: <a href="https://doi.org/10.5281/zenodo.3478143">https://doi.org/10.5281/zenodo.3478143</a> .</p> <p>The archive file contains:</p> <ul> <li><code>grid_ABCD.dat</code> : recorded coefficients A, B, C, D (on p+,p- grid in units of QED plasma temperature)</li> <li><code>interpolation.c</code> : code to interpolate and calculate the (integrated) energy density transfer rates</li> <li><code>aux/...</code> : additional files needed for multidimensional integration routine "<a href="https://github.com/stevengj/cubature/">cubature</a>"</li> </ul>
Particle trajectories - Freilich et al. "Diversity of growth rates maximizes phytoplankton productivity in an eddying ocean"
<p>The files provided here are the offline particle trajectories analyzed in Freilich, Flierl, and Mahadevan “Diversity of growth rates maximizes phytoplankton productivity in an eddying ocean”</p> <p>Both files are sqlite databases containing information about the same particle trajectories which are identified by the variable “iD”</p> <p> </p> <p>ini_day135_z115_forward_biology.db contains nutrient concentration on particle trajectories. A different biological rate lambda is used for each variable denoted NX where X is 0-13. The rates are: 0.015,0.075,0.15,0.3,0.75,1.5,3,10,15,20,50,75,100,120</p> <p>The variable DOY is the model day. </p> <p> </p> <p>ini_day135_z115_physical_forward.db contains the physical variables on particle trajectories. The variables are:</p> <p>x - east-west position</p> <p>y - north-south position</p> <p>z - vertical position</p> <p>u - east-west velocity</p> <p>v - north-south velocity</p> <p>w - vertical velocity</p> <p>vorticity - vertical component of relative vorticity</p>
CN-N (version 1): a crop-specific, 1 km-resolution nitrogen rate data product in China over 2004–2016
<p>CN-N version 1: A dataset of crop-specific, 1 km resolution nitrogen rate for rice, wheat and maize in China over 2004-2016 </p>
Figure 2: Variation of the shear stress depending on the speed rate 54-STUDIES TOWARDS OBTAINING A PHOTOPROTECTIVE DERMO-COSMETIC COMPLEX PRODUCT WITH NATURAL EXTRACTS OF INORGANIC AND ORGANIC SUBSTANCES
<p>The evaluation of photodegradation was carried out through the variation<br> of photoprotective factor of the studied product kept 60 minutes under UV<br> radiation at 65±C. The tests revealed the preservation or even a slight increase<br> in the SPF. The use of screen substances in the formulation of photoprotective<br> products results in undesirable sensory characteristics: visible white ¯lm on the<br> skin surface, unpleasant sensation, dry or oily skin after application.</p>
Figure 3: Viscosity variation depending on speed rate Table-STUDIES TOWARDS OBTAINING A PHOTOPROTECTIVE DERMO-COSMETIC COMPLEX PRODUCT WITH NATURAL EXTRACTS OF INORGANIC AND ORGANIC SUBSTANCES-
<p>Microbiological characteristics The total number of aerobic germs and fungi<br> was determined by the decimal dilution method or the multiple tube test. For<br> identifying pathogenic species we have used speci¯c tests (table6).<br> The evaluation of photodegradation was carried out through the variation<br> of photoprotective factor of the studied product kept 60 minutes under UV<br> radiation at 65±C. The tests revealed the preservation or even a slight increase<br> in the SPF. The use of screen substances in the formulation of photoprotective<br> products results in undesirable sensory characteristics: visible white ¯lm on the<br> skin surface, unpleasant sensation, dry or oily skin after application.</p>
Laboratory measurements of nitrous oxide production rates in agricultural soils from Lancaster, PA, estuarine sediments from the Scheldt Estuary Belgium/Netherlands, and estuarine soils from the Delaware River NJ under gradients of physicochemical perturbation
A set of experiments was performed to test 1) how various physicochemical perturbations (salinity, zinc, temperature, soil moisture, and pH) influenced denitrification and nitrous oxide production on short timescales (<1 day) in agricultural soils from Lancaster, PA, USA, 2) how variation in a single parameter (salinity) influenced rates of denitrification and nitrous oxide production in sediments that experience a range in that parameter (tidal freshwater, oligohaline, and mesohaline estuarine sediments from the Scheldt River estuary Belgium/Netherlands) on short timescales (< 1 day), and 3) how denitrification and nitrous oxide production along with key functional gene expression in tidal freshwater estuarine soils from the Delaware River, NJ, USA responded to a long-term (6 month) change in a single parameter (salinity) in a press experiment with subsequent short-term (< 1 day) pulses. In the final long-term experiment, nitrite reductase (nirS) and nitrous oxide reductase (nosZ) gene expression were also measured at three timepoints (days 7, 35, and 110).
The effects of nitrogen and warming on inorganic nitrogen pool and production rates in arctic and boreal ecosystems: inorganic nitrogen transformation during a 3-month laboratory incubation
We incubated (2006) northern Alaskan soils (boreal and tundra) at two temperatures (5 degC and 15 degC) and two levels of nitrogen addition (with and without) to directly test for nitrogen limitation of inorganic nitrogen production rate and explore the interaction between temperature and nitrogen limitation. Over the 3-month laboratory incubation, we measured initial extratable inorganic nitrogen and inorganic nitrogen production rates from organic and mineral soils from four different ecosystem types (boreal burned, boreal unburned, moist acidic, moist non-acidic). To charactarize the soils, we also measured total C, total N, microbial biomass, isotopes values (delta 13, delta14), total free amino acid, and total soluble protein.
A brief self-rating scale for the assessment of individual differences in gesture perception and production
<p>Data related to the following publication:</p> <p>Nagels, A., <strong>Kircher, T.</strong>, Steines, M., Grosvald, M., & <strong>Straube, B.</strong> (2015). A brief self-rating scale for the assessment of individual differences in gesture perception and production. <em>Learning and Individual Differences, 39</em>, 73–80.</p> <p> </p> <p>The Statistical Package for Social Sciences (SPSS) software was applied to perform a Principal Component Analysis (PCA) with varimax rotation.</p> <p>SPSS file: BAG_all_data_220_online.sav includes all relevant data of the E-scale (EP1-EP25) and the BAG scale (GE1-GE12).</p> <p>SPSS script: Syntax_BAG_analyses.sps includes the relevant scripts.</p> <p> </p>
Species-level termite methane production rates
<p>Termites consume substantial amounts of plant material across tropical and subtropical ecosystems. During the process of lignocellulose digestion, the symbiotic methanogenesis within termites' guts produces the potent greenhouse gas methane (CH4). Termites contribute an estimated 1-5% of global CH4 emissions, with these estimates derived from the product of termite biomass and termite CH4 production rate per unit of termite biomass. However, termite CH4 production rates vary significantly across species, genus, family, and feeding group, yet our understanding of this variation remains poor. Here, we reviewed papers published from 1975 to 2021 to create a single consistently derived list of species-level termite CH4 production rates. We searched Google Scholar using two key words: termite AND methane. We only included studies that had measured termite CH4 production rates using the incubation method. For each eligible study, we extracted and tabulated termite CH4 production rates and other relevant variables (e.g., feeding groups). We used μg CH4 g-1(termite) h-1 as the standardized unit, and if other units were presented, we converted them into this standardized unit. Overall, These data include 134 termite species from 65 genera and 5 families. Termite CH4 production rates ranged from 0 to 25.26 μg CH4 g-1(termite) h-1, with an average rate of 3.74 (standard deviation = 4.08, n = 251). Reported CH4 production rates were largely concentrated in the family Termitidae. Across feeding groups, soil feeders tended to have higher CH4 production rates than wood feeders. However, published data represent fewer than 5% of described termite species, and therefore we hope that our study will initiate a community-wide effort to fill data gaps and advance our understanding of the role of termites in critical biogeochemical cycles and other ecosystem processes.</p>
Potential Methane Production and Oxidation Rates and Porewater Chemistry Across Peatland Hummocks and Lawns
<p>This dataset contains potential methane (CH<sub>4</sub>) production and oxidation rates and porewater chemistry (dissolved oxygen, pH, redox potential, dissolved CH<sub>4</sub>, and CH<sub>4</sub> stable isotopes) measurements collected from hummocks and lawns in a poor fen in New Hampshire, USA. Potential CH<sub>4</sub> production and oxidation rates determined via incubations and dissolved oxygen measurements were collected in July 2018. Porewater CH<sub>4</sub> concentration, δ<sup>13</sup>C-CH<sub>4</sub> and δD-CH<sub>3</sub>D, and Eh/pH were collected in July/August 2020. The data file contains a "README" tab with a guide for variable units and descriptions. </p>
Supplemental information and Data for: Colloidal physics modeling reveals how per-ribosome productivity increases with growth rate in E. coli
<p>Faster growing cells must synthesize proteins more quickly. Increased ribosome abundance only partly accounts for increases in total protein synthesis rates. The productivity of individual ribosomes must increase too, almost doubling by an unknown mechanism. Prior models point to diffusive transport as a limiting factor but surface a paradox: faster growing cells are more crowded, yet crowding slows diffusion. We suspected physical crowding, transport, and stoichiometry, considered together, might reveal a more nuanced explanation. To investigate, we built a first-principles physics-based model of <em>E. coli</em> cytoplasm in which Brownian motion and diffusion arise directly from physical interactions between individual molecules of finite size, density, and physiological abundance. Using our microscopically-detailed model, we predict that physical transport of individual ternary complexes accounts for ~80% of translation elongation latency. We also find that volumetric crowding increases at faster growth even as cytoplasmic mass density remains relatively constant. Despite slowed diffusion, we predict that improved proximity between ternary complexes and ribosomes wins out, illustrating a simple physics-based mechanism for how individual elongating ribosomes become more productive. We speculate how crowding imposes a physical limit on growth rate and undergirds cellular behavior more broadly. Unfitted colloidal-scale modeling offers systems biology a complementary "physics engine" for exploring how cellular-scale behaviors arise from physical transport and reactions among individual molecules.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.