22 papers · ranked by Valyu relevance
Silin Chen, Ziqian Bi, Junyu Liu, Benji Peng + 13 more
Mathematics Fundamental: From Theory to Practice Authors: ['Silin Chen' 'Ziqian Bi' 'Junyu Liu' 'Benji Peng' 'Sen Zhang' 'Xiaoyong Pan' 'Jiawei Xu' 'Jinlang Wang' 'Keyu Chen' 'Caitlyn Heqi Yin' 'Pohsun Feng' 'Yizhu Wen' 'Tianyang Wang' 'Ming Li' 'Jin‐Tao Ren' 'Qian Niu' 'Ming Liu'] | I | | Python Data Structures and…
Oscar Castro, Pierrick Bruneau, Jean-Sébastien Sottet, Dario Torregrossa
'Dario Torregrossa'] Python has become the prime language for application development in the Data Science and Machine Learning domains. However, data scientists are not necessarily experienced programmers. While Python lets them quickly implement their algorithms, when moving at scale, computation efficiency becomes…
Weibing Wang, Junping Li, Yusen Ye, Lin Gao
Background Recent advances in high-resolution Hi-C and Micro-C technologies have enabled finer-scale characterization of 3D genome architecture. However, these improvements also introduce substantial computational challenges, as the memory requirements of Hi-C/Micro-C contact matrices scale quadratically with…
Knut Rand, Ivar Grytten, Milena Pavlovic, Chakravarthi Kanduri + 1 more
Python is a popular and widespread programming language for scientific computing, in large part due to the powerful array programming library NumPy, which makes it easy to write clean, vectorized and efficient code for handling large datasets. A challenge with using array programming for biological data is that the…
Yingyao Zhou, Jiayi Cox, Bin Zhou, Steven Zhu + 3 more
AlphaFold 2 uses 2D and 3D NumPy arrays to model a protein structure ([btae654-F1]), in contrast to Biopython’s model-chain-residue-atom tree structure ([btae654-F1]). This avoids the overhead of using nested boilerplate loops to extract atom coordinates. Displacement calculations with the ready-to-operate NumPy arrays…
Srinath Kailasa, Tingyu Wang, Lorena A. Barba, Timo Betcke
—Numba is a game-changing compiler for high-performance computing with Python. It produces machine code that runs outside of the single-threaded Python interpreter and that fully utilizes the resources of modern CPUs. This means support for parallel multithreading and auto-vectorization if available, as with compiled…
Maximilian H. Kriebel, Paweł Tecmer, Marta Gałyńska, Aleksandra Leszczyk + 1 more
Coupled-Cluster Implementations: A Comparison Between CPUs and GPUs Authors: Maximilian H. Kriebel, Paweł Tecmer, Marta Gałyńska, Aleksandra Leszczyk, Katharina Boguslawski In this work, we benchmark several Python routines for time and memory requirements to identify the optimal choice of the tensor contraction…
Fabian Woller, Lis Arend, Christian Fuchsberger, Markus List + 1 more
A range of computational tools in Python, including NumPy , SciPy , Pingouin , and pandas , is available for conducting statistical tests, yet each comes with specific limitations concerning our use case (Table [tbl1]). NumPy and pandas, two popular Python libraries for data handling and modeling, are largely limited…
Andrés Gersnoviez, Enzo Rucci
Currently, Python is one of the most widely used languages in various application areas. However, it has limitations when it comes to optimizing and parallelizing applications due to the nature of its official CPython interpreter, especially for CPU-bound applications. To solve this problem, several alternative…
Sonja Mathias, Adrien Coulier, Andreas Hellander
Background Cell-based models are becoming increasingly popular for applications in developmental biology. However, the impact of numerical choices on the accuracy and efficiency of the simulation of these models is rarely meticulously tested. Without concrete studies to differentiate between solid model conclusions and…
Zao Liu, Zhiwei Chen, Kan Song
Background Software for nuclear magnetic resonance (NMR) spectrometers offer general functionality of instrument control and data processing; these applications are often developed with non-scripting languages. NMR users need to flexibly integrate rapidly developing NMR applications with emerging technologies.…
Brandon M. Pardi, Syeda Tajin Ahmed, Silvia Jonguitud Flores, Warren Flores + 3 more
Here, we present a Python based software that allows for the rapid visualization, data mining, and basic model applications of quartz crystal microbalance with dissipation data. Our implementation begins with a Tkinter GUI to prompt the user for all required information, such as file name/location, selection of…
Chaoming Wang, Xiaoyu Chen, Tianqiu Zhang, Si Wu
The neural mechanisms underlying brain functions are extremely complicated. Brain dynamics modeling is an indispensable tool for elucidating these mechanisms by modeling the dynamics of the neural circuits that execute brain functions. To ease and facilitate brain dynamics modeling, a general-purpose programming…
Baidyanath Kundu, Vassil Vassilev, W. Lavrijsen
The simplicity of Python and the power of C++ force stark choices on a scientific software stack. There have been multiple developments to mitigate language boundaries by implementing language bindings, but the impedance mismatch between the static nature of C++ and the dynamic one of Python hinders their…
Yajushi Khurana, Keisuke Ishihara
Three-dimensional biological morphologies encode functional and physiological state, yet the directional, orientational, and topological properties of these shapes are rarely captured by morphometric tools available for bioimage analysis. Minkowski tensors are mathematically rigorous tensor-valued measures that encode…
Michael F. Adamer, Eljas Roellin, Lucie Bourguignon, Karsten Borgwardt
In many modern bioinformatics applications, such as statistical genetics, or single-cell analysis, one frequently encounters datasets which are orders of magnitude too large for conventional in-memory analysis. To tackle this challenge, we introduce SIMBSIG, a highly scalable Python package which provides a…
Nezar Abdennur, Geoffrey Fudenberg, Ilya Flyamer, Aleksandra A. Galitsyna + 3 more
Genomic intervals are one of the most prevalent data structures in computational genome biology, and used to represent features ranging from genes, to DNA binding sites, to disease variants. Operations on genomic intervals provide a language for asking questions about relationships between features. While there are…
Authors not listed
nDTomo is a Python-based software suite for the simulation, reconstruction and analysis of X-ray chemical imaging and computed tomography data. It provides a collection of Python function-based tools designed for accessibility and education as well as a graphical user interface (GUI). Prioritising transparency and ease…
Authors not listed
Solving optimization problems, especially for nonlinear and constrained systems, is a challenge. Decades of specialized algorithms have been developed for general and special cases of root finding, minimization (including constraints), for parameter estimation, and mapping connected spaces. These approaches typically…
Eric Hermes, Khachik Sargsyan, Habib Najm, Judit Zádor
We present a new algorithm for the optimization of molecular structures to saddle points on the potential energy surface using a redundant internal coordinate system. This algorithm automates the procedure of defining the internal coordinate system, including the handling of linear bending angles, e.g. through the…
Authors not listed
Inverse problems, where we seek the values of inputs to a model that lead to a desired set of outputs, are a challenges subset of problems in science and engineering. In this work we demonstrate the use of two generative AI methods to solve inverse problems. We compare this approach to two more conventional approaches…
I. Osborne, J. Pivarski, Ioana Ifrim, Angus Hollands + 1 more
'Henry Schreiner'] > Abstract. Awkward Array is a library for performing NumPy-like computations on nested, variable-sized data, enabling array-oriented programming on arbitrary data structures in Python. However, imperative (procedural) solutions can sometimes be easier to write or faster to run. Performant imperative…