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opencc-zeroDec 2021View details →

Mimulus cardinalis plasticity analyses and R scripts for: Spatial variation in high temperature-regulated gene expression predicts evolution of plasticity with climate change in the scarlet monkeyflower

A major way that organisms can adapt to changing environmental conditions is by evolving increased or decreased phenotypic plasticity. In the face of current global warming, more attention is being paid to the role of plasticity in maintaining fitness as abiotic conditions change over time. However, given that temporal data can be challenging to acquire, a major question is whether evolution in plasticity across space can predict adaptive plasticity across time. In growth chambers simulating two thermal regimes, we generated transcriptome data for western North American scarlet monkeyflowers (Mimulus cardinalis) collected from different latitudes and years (2010 and 2017) to test hypotheses about how plasticity in gene expression is responding to increases in temperature, and if this pattern is consistent across time and space. Supporting the genetic compensation hypothesis, individuals whose progenitors were collected from the warmer-origin northern 2017 descendant cohort showed lower thermal plasticity in gene expression than their cooler-origin northern 2010 ancestors. This was largely due to a change in response at the warmer (40ºC) rather than cooler (20ºC) treatment. A similar pattern of reduced plasticity, largely due to a change in response at 40ºC, was also found for the cooler-origin northern versus the warmer-origin southern population from 2017. Our results demonstrate that reduced phenotypic plasticity can evolve with warming and that spatial and temporal changes in plasticity predict one another.

opencc-zeroDec 2021View details →

An updated life history scheme for marine fishes predicts recruitment variability and sensitivity to exploitation

Aim: Patterns of population renewal in marine fishes are often irregular and lead to volatile fluctuations in abundance that challenge management and conservation efforts. Here, we examine the relationship between life history strategies and recruitment variability in exploited marine fish species using a macroecological approach. Location: Global ocean. Time period: 1950-2018. Major taxa studied: Bony and cartilaginous fish. Methods: Based on trait data for 244 marine fish species, we objectively extend the established Equilibrium-Periodic-Opportunistic (E-P-O) life history classification scheme to include two additional emergent life history strategies: "Bet-hedgers" (B) and Salmonic (S) strategists. B strategists include Rockfishes and other species inhabiting patchy benthic habitats with life histories that blend characteristics of E and P species; they combine very long lifespans with elevated investments in both parental care and fecundity. S strategists are comprised of mostly salmonids that share life history characteristics with E and O species: elevated investments in parental care reminiscent of E strategists, but with reduced fecundity and short lifespans characteristic of O species. We analyzed how the E-B-P-O-S life history classification mapped onto patterns of recruitment variability observed in population time series data (n = 156 species). Results: Generalized linear models suggest that life history strategy explains a modest, yet significant amount of recruitment variability across species. Greater predictive power arose after controlling for increased recruitment variance associated with variable fishing pressure, with O strategists showing the strongest sensitivity. B strategists were similarly susceptible to exploitation as P stocks, but their longer times to maturity make them particularly vulnerable to overfishing. Main conclusions: A broader recognition of the distinct ecology of Salmonic and Bet-hedger groups is important when studying life history strategies in marine fish. More generally, our results stress the importance of considering life history strategies for understanding patterns of recruitment variability across fish stocks.

opencc-by-4.0Dec 2021View details →

Raw data for "A-Proof-of -Concept: In vivo Volatile Organic Compounds Secretion Monitoring as a Tool for Prediction of Natural Pest Control Ability"

This upload refers to work entitled "A-Proof-of -Concept: In vivo Volatile Organic Compounds Secretion Monitoring as a Tool for Prediction of Natural Pest Control Ability" and contains the unprocessed data obtained during experiments perform.

Predicting Properties of Periodic Systems from Cluster Data: A Case Study of Liquid Water

<ul> <li> Description</li> </ul> The 1520 water clusters were extracted from Ref. 1. The respective energies and atomic forces were recomputed at the revPBE-D3/def2-TZVP [2-6], B3LYP-D3/def2-TZVP [4-6, 7, 8], and  BLYP-D3/def2-TZVP [4-6, 7, 9] level. <ul> <li> Format</li> </ul> The data is stored in python compressed array format (.npz) with the atomization energy in kcal/mol and atomic forces in kcal/mol/Ang. The data set contains five np.ndarray <pre><code>import numpy as np data = np.load('revpbe.npz') data['R'] # Cartesian coordinates of nuclei in Ang. data['E'] # Total energy in kcal/mol data['F'] # Atomic forces in kcal/mol/Ang. data['N'] # Number of atoms in each structure data['Z'] # Nuclear charges</code></pre> References <ul> </ul> [1] Molpeceres G., Zaverkin V., and Kästner J., “Neural-network assisted study of nitrogen atom dynamics on amorphous solid water – I. adsorption and desorption,” Mon. Not. R. Astron. Soc. 499, 1373 (2020). [2] P. E. Blöchl, “Projector augmented-wave method,” Phys. Rev. B 50, 17953 (1994). [3] Y. Zhang and W. Yang, “Comment on “generalized gradient approximation made simple”,” Phys. Rev. Lett. 80, 890 (1998). [4] S. Grimme, J. Antony, S. Ehrlich, and H. Krieg, “A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu,” J. Chem. Phys. 132, 154104 (2010). [5] F. Weigend and R. Ahlrichs, “Balanced basis sets of split valence, triple zeta valence and quadruple zeta valence quality for H to Rn: Design and assessment of accuracy,” Phys. Chem. Chem. Phys. 7, 3297 (2005). [6] F. Weigend, “Accurate Coulomb-fitting basis sets for H to Rn,” Phys. Chem. Chem. Phys. 8, 1057 (2006). [7] A. D. Becke, “Density-functional thermochemistry. iii. the role of exact exchange,” J. Chem. Phys. 98, 5648 (1993). [8] P. J. Stephens, F. J. Devlin, C. F. Chabalowski, and M. J. Frisch, “Ab initio calculation of vibrational absorption and circular dichroism spectra using density functional force fields,” J. Phys. Chem. 98, 11623 (1994). [9] C. Lee, W. Yang, and R. G. Parr, “Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density,” Phys. Rev. B 37, 785 (1988).

The prediction data analyzed in the article: "An improved regional coupled modeling system for Arctic sea ice simulation and prediction: a case study for 2018"

The outputs of seasonal predictions with the Coupled Arctic Prediction System version 1 analyzed in the article, "An improved regional coupled modeling system for Arctic sea ice simulation and prediction: a case study for 2018", including: Sea ice concentration (SIC) Sea ice thickness (SIT) Sea surface temperature (SST) Ice mass budget diagnostics Accumulated downward shortwave radiation at the surface (ASWDN) Accumulated downward longwave radiation at the surface (ALWDN) Near surface air temperature (T2)  Temperature and salinity profile of the upper ocean under sea ice

openmit-licenseJan 2022View details →

kipoi test predictions for DeepSTARR

During nightly tests, this file will be downloaded and compared against the predictions made by the kipoi model

Data from: Sperm metabolic rate predicts female mating frequency across Drosophila species

Female mating rates vary widely, even among closely related species, but the reasons for this variation are not fully understood. Across Drosophila species, female mating frequencies are positively associated with sperm length. This association may be due in part to sperm limitation, with longer-spermed species transferring fewer sperm, or to cryptic female choice. However, a previously overlooked factor is sperm metabolic rate, which may correlate with sperm length. If faster-metabolizing sperm accumulate age-related cellular damage more quickly, then females should remate sooner to obtain fresh sperm. Alternatively, frequent female mating may select for increased sperm competitiveness via increased metabolism. Here, we measure sperm metabolism across 13 Drosophila species and compare these measures to published data on female mating rate and on sperm length. Using fluorescent lifetime imaging microscopy, we quantify NAD(P)H metabolism ex vivo, in intact organs. Phylogenetically controlled regression reveals that sperm metabolic rate is positively associated with sperm length and with female mating frequency. Path analysis shows sperm length driving sperm metabolism and sperm metabolism either driving or being driven by female mating rate. While the causal directionality of these relationships remains to be fully resolved, and the effect of sperm metabolism on sperm aging and/or sperm competitiveness remains to be established, our results demonstrate the importance of sperm metabolism in sexual selection.

Island biogeography predicts skull gigantism and shape variation in meadow voles (Microtus pennsylvanicus) through ecological release and allometry

Island Rule describes the graded trend of gigantism in small-bodied species to dwarfism in large-bodied species inhabiting islands, but causal explanations remain unresolved. We used geometric morphometrics to quantify cranial morphology of 544 meadow vole (Microtus pennsylvanicus) samples across 11 island and 3 mainland populations from the Outer Lands of New England (Atlantic) and the Alexander Archipelago of Alaska (Pacific). We compared the thermoregulation and endurance (TRE) and ecological release (ER) hypotheses using all-subsets linear models employing residual randomization permutation procedures (rrpp), and Akaike Information Criterion (AIC) for model selection. We decoupled direct and indirect effects of island variables on size using path analysis. We evaluated shape with Principal Components Analysis (PCA) and Procrustes ANOVA on Procrustes shape coordinates, then assessed the impact of static allometry and TRE and ER variables on shape. Six Atlantic island populations exhibit significant signals of gigantism with the largest voles occurring on the smallest islands lacking predators. ER explains 63% of cranial size differences. Island area has a significant total effect on size by influencing the number of mammalian predators, resulting in a 0.011 increase in unit centroid size for a 100 km2 decrease in island area. This corresponds to a predicted 0.9% change in size for every 100 km2. Given static allometry, cranial shape does not respond to insularity independent of size. These results suggest that Island Rule is a latent evolutionary process whose manifestation depends on nuanced biogeographic and ecological contexts that have important conservation and taxonomic implications.

Data from: Predicting habitat suitability and connectivity for management and conservation of urban wildlife: A real-time web application for grassland water voles

<ol> <li>Natural habitats in urban areas provide benefits for both humans and biodiversity. However, to achieve biodiversity gains we require new techniques to determine habitat suitability and ecological connectivity that will inform urban planning and development.</li> <li>Using an example of an urban population of water voles (Arvicola amphibius) we developed a habitat suitability model and a resistance-surface-based model of landscape connectivity to identify potential connectivity between areas of suitable habitat. We then updated the environmental variables according to new urban development plans and used our models to generate spatially explicit predictions of both habitat suitability and connectivity.</li> <li>To make models accessible to urban and conservation planners we developed an interactive mapping tool that provided users with a graphical user interface (GUI) to inform conservation planning for this species.</li> <li>The model found that habitat suitability for water voles was related to distance from key environmental variables, such as built-up areas and urban green spaces, while the connectivity model identified important corridors connecting areas of potential distribution for this species.</li> <li>Future development plans altered the potential spatial distribution of the water vole population, reducing the extent of suitable habitat in some core areas. The interactive mapping tool made available suitable habitat and connectivity maps for conservation managers to assess new planning applications and for the development of a conservation action plan for water voles.</li> <li>Synthesis and applications: We believe this approach provides a framework for future development of nature conservation tools that can be used by planners to inform ecological decision making, increase biodiversity and reduce human-wildlife conflict in urban environments.</li> </ol>

DATASET RELATED TO ARTICLE "Brain Tumor Resection in Elderly Patients Potential Factors of Postoperative Worsening in a Predictive Outcome Model"

clinical database including information on patients included in the study at title

Data from: Watershed classification predicts streamflow regime and organic carbon dynamics in the Northeast Pacific Coastal Temperate Rainforest

Watershed classification has long been a key tool in the hydrological sciences, but few studies have been extended to biogeochemistry. We developed a combined hydro-biogeochemical classification for watersheds draining to the coastal margin of the Northeast Pacific coastal temperate rainforest (1,443,062 km2), including 2,695 small coastal rivers (SCR) and 10 large continental watersheds. We used cluster analysis to group SCR watersheds into 12 types, based on watershed properties. The most important variables for distinguishing SCR watershed types were evapotranspiration, slope, snowfall, and total precipitation. We used both streamflow and dissolved organic carbon (DOC) measurements from rivers (n = 104 and 90 watersheds respectively) to validate the classification. Watershed types corresponded with broad differences in streamflow regime, mean annual runoff, DOC seasonality, and mean DOC concentration. These links between watershed type and river conditions enabled the first region-wide empirical characterization of river hydro-biogeochemistry at the land-sea margin, spanning extensive ungauged and unsampled areas. We found very high annual runoff (mean > 3000 mm, n = 10) in three watershed types totaling 59,024 km2 and ranging from heavily glacierized mountain watersheds with high flow in summer to a rain-fed mountain watershed type with high flow in fall-winter. DOC hotspots (mean > 4 mg L-1, n = 14) were found in three other watershed types (48,557 km2) with perhumid rainforest climates and less-mountainous topography. We described four patterns of DOC seasonality linked to watershed hydrology, with fall-flushing being widespread. Hydro-biogeochemical watershed classification may be useful for other complex regions with sparse observation networks.

VESPAl Prediction of the human proteome (downloaded 22/01/17)

VESPAl Prediction of the human proteome (downloaded 22/01/17) generated with https://github.com/Rostlab/VESPA. For details on VESPAl see <blockquote> Marquet, C., Heinzinger, M., Olenyi, T. et al. Embeddings from protein language models predict conservation and variant effects. Hum Genet (2021). https://doi.org/10.1007/s00439-021-02411-y </blockquote> 3 proteins (Q8WZ42,Q8WXI7,Q8NF91) of the human proteome were too long to generate ProtT5 embeddings (Elnaggar et al. 2021). VESPAl predictions are therefore available for 20357 proteins.

ApacheJIT: A Large Dataset for Just-In-Time Defect Prediction

ApacheJIT: A Large Dataset for Just-In-Time Defect Prediction This archive contains the ApacheJIT dataset presented in the paper "ApacheJIT: A Large Dataset for Just-In-Time Defect Prediction" as well as the replication package. The paper is submitted to MSR 2022 Data Showcase Track. The datasets are available under directory dataset. There are 4 datasets in this directory. <ol> <li>apachejit_total.csv: This file contains the entire dataset. Commits are specified by their identifier and a set of commit metrics that are explained in the paper are provided as features. Column buggy specifies whether or not the commit introduced any bug into the system.</li> <li>apachejit_train.csv: This file is a subset of the entire dataset. It provides a balanced set that we recommend for models that are sensitive to class imbalance. This set is obtained from the first 14 years of data (2003 to 2016).</li> <li>apachejit_test_large.csv: This file is a subset of the entire dataset. The commits in this file are the commits from the last 3 years of data. This set is not balanced to represent a real-life scenario in a JIT model evaluation where the model is trained on historical data to be applied on future data without any modification.</li> <li>apachejit_test_small.csv: This file is a subset of the test file explained above. Since the test file has more than 30,000 commits, we also provide a smaller test set which is still unbalanced and from the last 3 years of data.</li> </ol> In addition to the dataset, we also provide the scripts using which we built the dataset. These scripts are written in Python 3.8. Therefore, Python 3.8 or above is required. To set up the environment, we have provided a list of required packages in file requirements.txt. Additionally, one filtering step requires GumTree [1]. For Java, GumTree requires Java 11. For other languages, external tools are needed. Installation guide and more details can be found <a href="https://github.com/GumTreeDiff/gumtree/wiki/Getting-Started">here</a>. The scripts are comprised of Python scripts under directory src and Python notebooks under directory notebooks. The Python scripts are mainly responsible for conducting GitHub search via GitHub search API and collecting commits through PyDriller Package [2]. The notebooks link the fixed issue reports with their corresponding fixing commits and apply some filtering steps. The bug-inducing candidates then are filtered again using gumtree.py script that utilizes the GumTree package. Finally, the remaining bug-inducing candidates are combined with the clean commits in the dataset_construction notebook to form the entire dataset. More specifically, git_token handles GitHub API token that is necessary for requests to GitHub API. Script collector performs GitHub search. Tracing changed lines and git annotate is done in gitminer using PyDriller. Finally, gumtree applies 4 filtering steps (number of lines, number of files, language, and change significance). References: 1. GumTree <ul> <li> <a href="https://github.com/GumTreeDiff/gumtree">https://github.com/GumTreeDiff/gumtree</a> </li> <li> Jean-Rémy Falleri, Floréal Morandat, Xavier Blanc, Matias Martinez, and Martin Monperrus. 2014. Fine-grained and accurate source code differencing. In ACM/IEEE International Conference on Automated Software Engineering, ASE ’14,Vasteras, Sweden - September 15 - 19, 2014. 313–324 </li> </ul> 2. PyDriller <ul> <li> <a href="https://pydriller.readthedocs.io/en/latest/">https://pydriller.readthedocs.io/en/latest/</a> </li> <li> Davide Spadini, Maurício Aniche, and Alberto Bacchelli. 2018. PyDriller: Python Framework for Mining Software Repositories. In Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering(Lake Buena Vista, FL, USA)(ESEC/FSE2018). Association for Computing Machinery, New York, NY, USA, 908–911 </li> </ul>

A Survival Analysis based Volatility and Sparsity Modeling Network for Student Dropout Prediction

KDDCup15.rar and XuetangX.rar are the metadata used in the paper "A Survival Analysis based Volatility and Sparsity ModelingNetwork for Student Dropout Prediction". Both of them have be drawn from the largest MOOC platform in China, XuetangX (see https://www.xuetangx.com/). If any interested parties want to fetch the original dataset, they may follow the URLs bellow: KDDCup 2015 dataset is available at <a href="https://www.biendata.xyz/competition/kddcup2015/data/">https://www.biendata.xyz/competition/kddcup2015/data/</a>. XuetangX dataset is available at <a href="http://moocdata.cn/data/user-activity">http://moocdata.cn/data/user-activity</a>.

A predictive flight-altitude model for avoiding future conflicts between an emblematic raptor and wind energy development in the Swiss Alps

Deployment of wind energy is proposed as a mechanism to reduce greenhouse gas emissions. Yet, wind energy and large birds, notably soaring raptors, both depend on suitable wind conditions. Conflicts in airspace use may thus arise between wind energy development and wildlife protection due to the risks of collisions of birds with the blades of wind turbines. Using locations of GPS-tagged bearded vultures, a rare scavenging raptor reintroduced into the Alps, we built a spatially-explicit model to predict potential areas of conflict with future wind turbines deployments in the Swiss Alps. We modelled the probability of bearded vultures flying within or below the rotor-swept zone of wind turbines as a function of wind and environmental conditions, including food supply (presence of wild ungulates). Flight activity at potential risk of collision was generally high, concentrating on south-exposed mountainsides, especially in areas where ibex carcasses have a high occurrence probability, with critical areas covering vast expanses throughout the Swiss Alps. Our model provides a spatially-explicit decision tool that will guide authorities and energy companies for planning the deployment of wind farms in a proactive manner to reduce risk to emblematic Alpine wildlife.

opencc-by-4.0Feb 2022View details →

Data supporting "Can Long-Term Experiments Predict Real Field N and P Balance and System Sustainability? Results from Maize, Winter Wheat, and Soybean Trials Using Mineral and Organic Fertilisers"

Data supporting "Can Long-Term Experiments Predict Real Field N and P Balance and System Sustainability? Results from Maize, Winter Wheat, and Soybean Trials Using Mineral and Organic Fertilisers" by Piccoli et al. (2021) Agronomy 2021, 11, 1472. https://doi.org/10.3390/agronomy11081472

opencc-zeroFeb 2022View details →

Comparative and predictive phylogeography in the South American diagonal of open formations: Unravelling the biological and environmental influences on multitaxon demography

Phylogeography investigates historical drivers of species' geographic distribution. Special attention has been given to ecological, climatic, and geological processes in the diversification of the Neotropical biota. Several species sampled across the dry diagonal of South America (DDSA, comprising the Caatinga, Cerrado, and Chaco biomes) experienced range shifts coincident with Quaternary climatic changes. However, studies across different spatial, temporal, and biological scales on species from South America's dry biomes are still poorly represented. Here, we combine phylogeographic model selection and machine learning predictive frameworks to investigate the influence of Pleistocene climatic changes on both plant and animal species from the DDSA. We assembled mitochondrial/chloroplastic DNA sequences in public repositories and inferred the historical demographic responses of 70 lineages. We then built a random forest model using both biotic and abiotic information to identify potential traits for predicting whether species underwent population expansion, contraction, or stasis during the Pleistocene. Finally, we estimated the temporal synchrony of species demographic responses using hierarchical approximate Bayesian computation (hABC). Biotic variables largely predicted how species responded to Pleistocene climatic changes, and demographic changes were mostly synchronous during the Middle Pleistocene. Although many DDSA species underwent demographic expansion, presumably associated with the spread of aridity during glacial Pleistocene periods, our findings suggest that some species exhibited the opposite response and that species-specific attributes might have been related to these differences.

opencc-by-4.0Dec 2021View details →

Ensemble Refinement of Stable-5-LOX and AlphaFold2 predictions including variants

Ensemble Refinement of Stable-5-LOX in "closed" (PDB code: 7TTK) and "open" (PDB code: 7TTJ) conformations. AlphaFold2 models of Stable-5-LOX and variants from the research article "Helical remodeling augments 5-lipoxygenase activity."

opencc-by-4.0Feb 2022View details →

PIGNet: A physics-informed deep learning model toward generalized drug-target interaction predictions

Training, test datasets of the paper "PIGNet: A physics-informed deep learning model toward generalized drug-target interaction predictions".