16 papers · ranked by Valyu relevance
Safoora Masoumi, Saeid Shahraz
Background Meta-analysis is a central method for quality evidence generation. In particular, meta-analysis is gaining speedy momentum in the growing world of quantitative information. There are several software applications to process and output expected results. Open-source software applications generating such…
Károly Bósa, Paul Heinzlreiter
Background Data preparation is a fundamental aspect of data engineering, a prerequisite for later tasks such as data visualization, reporting, and training machine learning models. Despite the recurring patterns in data transformation processes, the specific steps often vary depending on the project context, data…
Jingyao Wang, Chuyuan Zhang, Ye Ding, Yuxuan Yang
—Artificial intelligence technology has already had a profound impact in various fields such as economy, industry, and education, but still limited. Meta-learning, also known as "learning to learn", provides an opportunity for general artificial intelligence, which can break through the current AI bottleneck. However…
Serena Cofano, Giacomo Benedetti, Matteo Dell’Amico
Our analysis highlights issues related to dependency versions, metadata files, remote dependencies, and optional dependencies. Additionally, we identified a systematic issue with the lack of standards for metadata in the PyPI ecosystem. This includes inconsistencies in the presence of metadata files as well as…
Joshua M. Mitchell, Yuanye Chi, Maheshwor Thapa, Zhiqiang Pang + 2 more
To standardize metabolomics data analysis and facilitate future computational developments, it is essential is have a set of well-defined templates for common data structures. Here we describe a collection of data structures involved in metabolomics data processing and illustrate how they are utilized in a…
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…
Parker Ladd Bremer, Oliver Fiehn, Hong-Yu Zhang
Metabolomics has advanced to an extent where it is desired to standardize and compare data across individual studies. While past work in standardization has focused on data acquisition, data processing, and data storage aspects, metabolomics databases are useless without ontology-based descriptions of biological…
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…
Weiyuntian Dai, Yonglin Yi, Anqi Lin, Chaozheng Zhou + 4 more
Meta-analysis is a common statistical method used to summarize multiple studies that cover the same topic. It can provide less biased results and explain heterogeneity between studies. Although there exists a variety of meta-analysis softwares, they are rarely both convenient to use and capable of comprehensive…
Joshua M. Mitchell, Yuanye Chi, Maheshwor Thapa, Zhiqiang Pang + 2 more
To standardize metabolomics data analysis and facilitate future computational developments, it is essential is have a set of well-defined templates for common data structures. Here we describe a collection of data structures involved in metabolomics data processing and illustrate how they are utilized in a…
Christian D. Powell, Hunter N. B. Moseley
Background An updated version of the mwtab Python package for programmatic access to the Metabolomics Workbench (MetabolomicsWB) data repository was released at the beginning of 2021. Along with updating the package to match the changes to MetabolomicsWB’s ‘mwTab’ file format specification and enhancing the package’s…
Nathan J. LeRoy, Oleksandr Khoroshevskyi, Aaron O’Brien, Rafał Stepień + 2 more
As biological data increases, we need additional infrastructure to share it and promote interoperability. While major effort has been put into sharing data, relatively less emphasis is placed on sharing metadata. Yet, sharing metadata is also important, and in some ways has a wider scope than sharing data itself. Here…
Gordon Grabert, Daniel Dehncke, Tushar More, Markus List + 5 more
Advances in high-throughput techniques have revolutionized the generation of molecular biology data. These developments facilitate longitudinal studies to investigate different levels of biological systems and disease-related system changes over time, for example in metabolism and gene regulation (, , ). Recent…
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…
Ramon van der Zwaan, Berdien van Olst, Mark C.M. van Loosdrecht, Martin Pabst
Microbial community proteomics is rapidly gaining traction as it allows exploration of functional processes in microbial ecosystems. Consequently, there is a growing need for user-friendly tools that enable performance evaluation and interactive visualization of the increasingly complex community proteomics data. We…
Bruno Farias, Rafael Menezes, Eddie B. de Lima Filho, Youcheng Sun + 1 more
'Lucas C. Cordeiro'] This paper introduces a tool for verifying Python programs, which, using type annotation and front-end processing, can harness the capabilities of a bounded model-checking (BMC) pipeline. It transforms an input program into an abstract syntax tree to infer and add type information. Then, it…