11 papers · ranked by Valyu relevance
Andrew Morin, Jennifer Urban, Piotr Sliz, Fran Lewitter
Source code is the human readable form of a computer programming language. “Open source” refers to licenses that require the source code be available to users, and that users be able to reuse, modify, and distribute the code . Without access to source code, researchers cannot effectively inspect, understand, or…
Authors not listed
Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms…
Mark Fingerhuth, Tomáš Babej, Peter Wittek, Leonie Anna Mueck
Open source software is becoming crucial in the design and testing of quantum algorithms. Many of the tools are backed by major commercial vendors with the goal to make it easier to develop quantum software: this mirrors how well-funded open machine learning frameworks enabled the development of complex models and…
Christine Årdal, Annette Alstadsæter, John-Arne Røttingen
Background Innovation through an open source model has proven to be successful for software development. This success has led many to speculate if open source can be applied to other industries with similar success. We attempt to provide an understanding of open source software development characteristics for…
Rita Kukafka, Neil Chue Hong, Simon Hettrick, Ye Ye + 21 more
Background The National Cancer Institute Informatics Technology for Cancer Research (ITCR) program provides a series of funding mechanisms to create an ecosystem of open-source software (OSS) that serves the needs of cancer research. As the ITCR ecosystem substantially grows, it faces the challenge of the long-term…
Authors not listed
The increasing importance and predictive power of modern molecular modeling, driven by physics- and machine learning-based methods, necessitates a new collaborative architecture to replace the isolated, traditional model of software development. The traditional approach often led to redundant engineering effort, high…
Eric Deibel
The introduction of open source in the life sciences is increasingly being suggested as an alternative to patenting. This is an alternative, however, that takes its shape at the intersection of the life sciences and informatics. Numerous examples can be identified wherein open source in the life sciences refers to…
Matthew H Todd
Scientific data are being generated and shared at ever-increasing rates. Two new mechanisms for doing this have developed: open access publishing and open source research. We discuss both, with recent examples, highlighting the differences between the two, and the strengths of both.
Authors not listed
Raman spectroscopy is an increasingly powerful and fast-growing analytical technique across diverse disciplines, from materials science and chemistry to biology and medicine, thanks to advances in Raman instrumentation and greatly supported by the flourishing of chemometrics and artificial intelligence (AI). However…
Christopher Woods, Lester Hedges, Adrian Mulholland, Maturos Malaisree + 10 more
Sire is a Python/C++ library that is used to both prototype new algorithms and as an interoperability engine for exchanging information between molecular simulation programs. It provides a collection of file parsers and information converters that together make it easier to combine and leverage the functionality of…
Authors not listed
The discoverability and reusability of data is critical for machine learning to drive new discovery in the chemical sciences, and the ‘FAIR Guiding Principles for scientific data management and stewardship’ provide a measurable set of guidelines that can be used to ensure the accessibility of reusable data. We…