15 papers · ranked by Valyu relevance
Venus N. Sherathiya, Michael D. Schaid, Jillian L. Seiler, Gabriela C. Lopez + 1 more
Fiber photometry (FP) is an adaptable method for recording in vivo neural activity in freely behaving animals. It has become a popular tool in neuroscience due to its ease of use, low cost, the ability to combine FP with freely moving behavior, among other advantages. However, analysis of FP data can be challenging for…
Alex Sheng
We develop a simple and straightforward methodology to create AI computer agents that can carry out diverse computer tasks and self-improve by developing tools and augmentations to enable themselves to solve increasingly complex tasks. As large language models (LLMs) have been shown to benefit from nonparametric…
Hanxing Ding, Shuchang Tao, Liang Pang, Zihao Wei + 4 more
Language Models Authors: ['Hanxing Ding' 'Shuchang Tao' 'Liang Pang' 'Zihao Wei' 'Jinyang Gao' 'Bolin Ding' 'Huawei Shen' 'Xueqi Chen'] Tool learning has emerged as a crucial capability for large language models (LLMs) to solve complex real-world tasks through interaction with external tools. Existing approaches face…
Thomas Donoghue, Sandra Maesta-Pereira, Claire Zhixian Han, Salman Ehtesham Qasim + 1 more
A common method of collecting and analyzing neural activity is to implant electrodes that record the electrical activity of the brain, from which action potentials of individual neurons can be recorded (). After pre-processing to detect spike waveforms and cluster them into groups representing putative single neurons…
Stephan Lukasczyk, Gordon Fraser
Automated unit test generation is a well-known methodology aiming to reduce the developers' effort of writing tests manually. Prior research focused mainly on statically typed programming languages like Java. In practice, however, dynamically typed languages have received a huge gain in popularity over the last decade.…
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…
Benjamin M. Gyori, Charles Tapley Hoyt
Understanding the complex molecular processes governing how cells respond to external stimuli crucially relies on prior knowledge about signaling, regulatory, and metabolic pathways. Standardized representations are necessary to exchange such pathway knowledge and allow interoperability between tools. BioPAX () is a…
Daewon Lee, Pier Luigi Martelli
A variety of real-world phenomena such as biological pathways, communication networks and social relationships can be represented as networks (). An insightful visualization of networks facilitates understanding of the analyzed networks and leads to important discoveries. Therefore, open-source software for analyzing…
Christopher Pyles, Francois van Schalkwyk, Gerard Gorman, Marijan Beg + 3 more
'Marijan Beg' 'Lee Stott' 'Nir Levy' 'Ran Gilad-Bachrach'] We continuously interact with computerized systems to achieve goals and perform tasks in our personal and professional lives. Therefore, the ability to program such systems is a skill needed by everyone. Consequently, computational thinking skills are essential…
Zejun Zhang, Zhenchang Xing, Xin Xia, Xiwei Xu + 1 more
Compared to other programming languages (e.g., Java), Python has more idioms to make Python code concise and efficient. Although pythonic idioms are well accepted in the Python community, Python programmers are often faced with many challenges in using them, for example, being unaware of certain pythonic idioms or do…
Mohammed Zniber, Youssef Fatihi, Tan-Phat Huynh, Sofia Forslund
Metabolomics is an emerging field within systems biology and represents the final step in the ‘omics’ cascade (, ). As a technology-driven discipline, metabolomics utilizes advancements in analytical chemistry and computational techniques to improve data collection, analysis, and interpretation (). Key platforms in…
Li Li, Jiawei Wang, Haowei Quan
Despite being the most popular programming language, Python has not yet received enough attention from the community. To the best of our knowledge, there is no general static analysis framework proposed to facilitate the implementation of dedicated Python static analyzers. To fill this gap, we design and implement such…
Wei Cheng, Xiangrong Zhu, Wei Hu
Code sharing and reuse is a widespread use practice in software engineering. Although a vast amount of open-source Python code is accessible on many online platforms, programmers often find it difficult to restore a successful runtime environment. Previous studies validated automatic inference of Python dependencies…
Jan Janssen, Janine George, Julian Geiger, Marnik Bercx + 7 more
Numerous Workflow Management Systems (WfMS) have been developed in the field of computational materials science with different workflow formats, hindering interoperability and reproducibility of workflows in the field. To address this challenge, we introduce here the Python Workflow Definition (PWD) as a workflow…
Wubin Ding, David Goldberg, Wanding Zhou
PyComplexHeatmap was designed to visualize matrix data and associated metadata through sophisticated, richly annotated heatmap layouts. We have integrated the R grammar-of-graphics semantics with the Python-native matplotlib/Pandas-based data science ecosystem, allowing users to utilize built-in matplotlib colormaps…