5 papers · ranked by Valyu relevance
Xuebin Feng, Emma R. Master
Sequence similarity networks (SSNs) are graphical representations of sequence relationship frequently used for exploring protein sequence space. Conventional SSN workflows typically use BLAST to calculate sequence similarities and rely on external visualization tools to generate the final networks. Consequently, raw…
Christoph Li, Josh Lawrimore, Dustin Moraczewski, Adam G. Thomas
labapi is a Python library that enables computational workflows to connect to LabArchives’ electronic lab notebook (ELN). Without an Application Programming Interface (API) connection, researchers must manually add workflow outputs through the LabArchives web interface, navigating to the appropriate page and uploading…
Eliezer Masliah
How transient neural representations become integrated and stable enough to function as internal neural models remains incompletely understood. Grounded in efficient coding, Bayesian and predictive frameworks, recurrent and attractor dynamics, neural state-space models, and systems neuroscience, the Principle of…
Xiaoyue Hu, Yuhao Ma, Ruixing Ming, Heping Zhang + 1 more
Identifying essential biomarkers remains a core challenge in elucidating the pathogenic mechanisms and achieving precise diagnosis of complex diseases. Deep neural networks offer immense predictive power, yet their lack of interpretability severely limits downstream biological insight. Here, we introduce DeepVaris, an…
Hayden Johnson, Boris A. Vinatzer, Reza Mazloom, Kassaye Belay + 2 more
Rapid and accurate microbial identification is critical for interpreting biological data in basic research and when making applied decisions on how to effectively treat patients and control human, animal, and plant diseases. Advancements in high-throughput sequencing have the potential to expedite fungal species…