Performance metrics for ProSmith and previously published methods for DTA prediction on the random split of the Davis dataset. by Alexander Kroll (9304225)

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Performance metrics for ProSmith and previously published methods for DTA prediction for different splitting scenarios. by Alexander Kroll (9304225)

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For accurate DTA predictions, ProSmith requires training on identical drugs but not on similar proteins. by Alexander Kroll (9304225)

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Coefficient of determination <i>R</i>² of ProSmith for different splitting scenarios of the Davis dataset. by Alexander Kroll (9304225)

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We divided the ESP test set into subsets according to the number of positive data points with the same small molecule in the training set. by Alexander Kroll (9304225)

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Performance metrics for ProSmith and ESP for the prediction of enzyme-substrate pairs. by Alexander Kroll (9304225)

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We divided the ESP test set into subsets according to the maximal sequence identity of an enzyme compared to all training enzymes. by Alexander Kroll (9304225)

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Drug-target affinity predictions improve with increasing drug similarity score compared to the training drugs. by Alexander Kroll (9304225)

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Performance metrics of ProSmith and previously published methods for the prediction of Michaelis constants <i>K</i>_M. by Alexander Kroll (9304225)

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Hyperparameters of the ProSmith Transformer Network. by Alexander Kroll (9304225)

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Enzyme-substrate pair predictions improve with increasing substrate similarity compared to training substrates. by Alexander Kroll (9304225)

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Optimal implementation of matrix operations on the CPU platform (double precision; solid black line = benchmarked bandwidth; lines + symbols = effective bandwidth; black = COPY2D;... by Xuzhen He (14676114)

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Model for the maximal effective bandwidth of numerical models (lines = model prediction by Eq 12; symbols = measured maximal effective bandwidth; filled = f64; hollow = f32; black... by Xuzhen He (14676114)

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Diagram of data analysis and implementation of the package BOOME. by Li-Pang Chen (9747423)

Slides: A better strategy for interpolating gravity and magnetic data by Santiago Rubén Soler (6476147)

“…</div><div><br></div><div>The source code developed for this study is based on the EQL implementation available in Harmonica (fatiando.org/harmonica), an open-source Python library for modelling and processing gravity and magnetic data. …”

Left schematic of the XOR gate implementation [11]. by Fabricio Cravo (21387854)

DataSheet1_Optimisation of Water-Energy Networks in Process Industry: Implementation of Non-Linear and Multi-Objective Models.PDF by Miguel Castro Oliveira (11975819)

“…In this work, two approaches for the solving of an optimisation problem related to the improvement of water and energy use in a process industry plant (three water-using processes) are implemented. These approaches consist on the development of a mixed-integer non-linear programming (MINLP) model and a multi-objective programming (MOP) model using the Python language. …”

Parallel scalable simulations of biological neural networks using TensorFlow: A beginner's guide by Rishika Mohanta (7327013)

“…<p>Biological neural networks are often modeled as systems of coupled, nonlinear, ordinary or partial differential equations. …”

Supporting data for "Interpreting complex ecological patterns and processes across differentscales using Artificial Intelligence" by Yifei Gu (9507104)

“…The detailed implementation, source code and demo dataset are included in dedicated folders for each chapter.…”

A high-performance and highly reusable fast multipole method library and its application to solvation energy calculations at virus-scale by Tingyu Wang (12342757)

“…It empowers researchers to compute solvation energy at the scale of viruses interactively via easy-to-use Python interfaces. The 1/N convergence rate observed in mesh-refinement studies confirms code correctness, and result comparison with other trusted PB software shows agreement using a wide range of proteins.Performance results report timings and breakdowns with between 8,000 and 2 million boundary elements and confirm the linear complexity in both time and space. …”