5 papers · ranked by Valyu relevance
Dianzhuo Wang, Qian Xu, Arjun Banerjee, Rishi Jain + 7 more
Inferring biological function from experimental data is central to understanding emerging pathogens and developing effective countermeasures, yet interpreting these data remains slow and expert-intensive. AI agents could help accelerate this process by reasoning across sequence, structural, and biophysical evidence. We…
Sergio Cabello, Panos Giannopoulos
We study the problem of searching for a target at some unknown location in $\mathbb{R}^d$ when additional information regarding the position of the target is available in the form of predictions. In our setting, predictions come as approximate distances to the target: for each point $p\in \mathbb{R}^d$ that the…
Weiying Ding, Qiang Shen, Yingjie Geng, Chak W. Kam
To evaluate the agreement between IMCI-predicted probabilities and the observed incidence of organ dysfunction progression within 24 h, calibration curves were constructed and Brier scores were calculated. The results demonstrated good concordance between the predicted probabilities generated by IMCI-A and the actual…
William JF Rieger, Sebastian Häussermann, Luca Herrmann, Zecheng Li + 8 more
Enzymes frequently exhibit promiscuous activity beyond their native roles, providing starting-points for new functions. Finding these promiscuous enzymes, especially for non-native chemical transformations, is challenging but highly valuable, as they promise novel, sustainable solutions for chemistry and biotechnology.…
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…