EMBO Reports - The predominant financial model for OA is based on Article Processing Charges (APCs), which often forces authors to assemble support from diverse sources, including research grants....

Lund University. This year marked the program’s third year, with visits to four international middle schools, Internationella Engelska Skolan (IES) Lund, IES Staffanstorp, Lund International School (L...

AI research in question as author claims to have written over 100 papers on AI that one expert calls a ‘disaster’

What are you most excited about for the next five years?The new kind of data which is becoming available, time-resolved multi-channel molecular data. Getting into dynamics opens up for addressing caus...

CAS MUDDE Det blir dyrt, politiserat – och dåliga matcher

This webinar introduces the KTH Data Repository and walks you through how you can use it to make your research data accessible and FAIR.

COP30 i Brasilien är FN:s 30:e toppmöte om klimatet. Mötet är det tionde sedan Parisavtalet och fokuserar på att utvärdera resultatet av de mål som sattes upp för att begränsa global uppvärmning. På p...

Full-text search across 15,000+ papers from top economics journals and NBER working papers. Track how empirical methods have evolved over time.

One of the papers in the analysis contained a figure (bottom) found to have overlap with other work by the same author (top). Both papers have been retracted. Annotated images: PubPeer More than 20…

Figure 1.

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, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.

Elicit.com, Consensus, and Undermind.ai are among the new leading comprehensive cross-disciplinary “AI-powered academic search engines” today.