6 papers · ranked by Valyu relevance
Namasi G Sankar, Georgios Miliotis, Simon Caton
Genome assembly is important in infectious disease surveillance, antimicrobial resistance monitoring, and cancer genomics. The task of reconstructing full genomic sequences from fragmented reads, can be framed as a large scale combinatorial optimisation problem. Recent advances in quantum computing have introduced new…
Jalaja Madhusudhanan, Anton Parinov, Charles Fieseler, Manuel Zimmer
Behavior arises from the interplay between spontaneous brain dynamics and sensory-driven responses, yet how spontaneous neural activity shapes variability in decision-making remains unclear. We leverage the tractable C. elegans nervous system to address this question. During oxygen avoidance, we observe binary…
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…
Hao Ding, Nannan Wu, Tianyi Qiu
DNA foundation models such as Evo2 7B adopt hybrid Hyena/attention architectures (Striped-Hyena2) whose single-stream autoregressive decoding is bounded by weight bandwidth at ∼45 tok/s. Speculative decoding on such hybrids faces a systems problem that prior SSM work solves only partially: after a draft is verified…
Fabio Barteri, Arcadi Navarro, Omar E. Cornejo
Continuous traits evolve unevenly across phylogenies, producing patterns of phenotypic differentiation shaped by both shared ancestry and lineage-specific change. Identifying exceptionally differentiated species pairs may therefore improve genome–phenome comparisons, but existing approaches rarely rank such contrasts…
Julius F. Witte, Artur Lissin, Isabel Schober, Christian Ebeling + 16 more
The vast amount of existing data on microbial strains holds immense potential to revolutionize bioindustry through the application of Artificial Intelligence (AI). However, the training of robust predictive AI models requires large-scale, unified, and non-redundant microbial datasets, which is currently severely…