9 papers · ranked by Valyu relevance
João Sartori, Eduardo Krempser, Ana Carolina Ramos Guimarães, Lucas de Almeida Machado
The optimization of protein sequences for enhanced binding and stability remains a formidable challenge in bioengineering due to the vastness of sequence space. Existing state-of-the-art methods, including traditional structure-based design and protein language models, use fitness estimators as objective functions to…
Albert Jiménez-Blanco, Lorién López-Villellas, Juan Carlos Moure, Miquel Moreto + 1 more
Sequence-to-graph alignment is a central problem in bioinformatics, with applications in multiple sequence alignment (MSA) and pangenome analysis, among others. However, current algorithms for optimal affine-gap alignment impose high memory and computational requirements, limiting their scalability to aligning long…
Ryo Tsuchihashi, Misaki Kinoshita
Cyclic peptides have emerged as a pivotal modality for next-generation therapeutics, due to their superior biocompatibility, high selectivity, and structural stability. While AI-driven peptide design has advanced rapidly, conventional optimization algorithms are often constrained by initialization biases, which impede…
Nicholas Tolley, Stephanie Jones
Recurrent neural networks (RNNs) have proven to be highly successful in emulating human-like cognitive functions such as working memory. In recent years, RNNs are evolving to incorporate more biophysical realism to produce more plausible predictions on how cognitive tasks are solved in real neural circuits. However…
Tianhao Chu, Yuling Wu, Neil Burgess, Zilong Ji + 1 more
Path integration is essential for spatial navigation. Experimental studies have identified neural correlates for path integration, but exactly how the neural system accomplishes this computation remains unresolved. Here, we adopt recurrent neural networks (RNNs) trained to perform a path integration task to explore…
Shanmukha Vamshi Kuruba, George Stephenson, Vignesh Kasinath
Multi-organelle segmentation in volumetric electron microscopy (vEM) faces several challenges, including severe class imbalance, the presence of small, rare classes, and inconsistent class coverage across crops. While recent work has focused primarily on architectural design, the impact of sampling, loss functions, and…
Yukun Yang, Wolfgang Maass
Most current methods for goal-directed action selection in the face of changing goals and contingencies require DNNs or LLMs. Therefore they are less suited for implementation in edge devices, where low energy-consumption is imperative. The brain shows that similar functionality can be produced with just 20W, even with…
Arseny Shur, Ido Tziony, Yaron Orenstein
Minimizers are sampling schemes which are ubiquitous in almost any high-throughput sequencing analysis. Assuming a fixed alphabet of size σ, a minimizer is defined by two positive integers k, w and a linear order ρ on k-mers. A sequence is processed by a sliding window algorithm that chooses in each window of length w…
Vincent P. Ferrera, Samuel Lippl, Kenneth Kay, Fabian Munoz + 3 more
Transitive inference (TI) is the ability to reason about transitive relationships in an ordered set of items (e.g., if A>B and B>C, then A>C). TI is widely held to depend on a linear representation of the serial (rank) order of those items. By what computational mechanism is such an ordering constructed during…