12 papers · ranked by Valyu relevance
Jose L Figueroa, Richard Allen White
We now exist in the era of massive datasets from genomics, large language models, and all the known knowledge of humanity right at our fingertips. Much of this data is becoming more accessible; however, processing such data remains an ongoing issue across systems including high performance computing (HPC)…
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Recent advances in machine learning force fields (MLFF) have significantly extended the reach of atomistic simulations. Continuous progress in this field requires reliable reference datasets, accurate MLFF architectures, and efficient active learning strategies to enable robust modeling of complex molecular and…
Ge Zhang
bcftools is the standard toolkit for handling VCF and BCF variant files, but it processes records on a single core; its --threads option speeds up only compression of the output, not the work done on variant records. Processing large call sets is therefore slow, and users often divide the genome and reassemble the…
G. Kandemir, D. H. Duncan, D. van Moorselaar, J. Theeuwes
For almost half a century, target-distractor similarity has been known to induce different visual search modes. When a target is highly salient, it can pop out, suggesting parallel processing of all items irrespective of set size. By contrast, high similarity among items requires item-by-item comparison with an…
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Free radical copolymerization, a crucial industrial technique for synthesizing copolymers from a diverse array of monomers with ease, has played a significant role in advancing human society. However, the journey from small-scale research and development to manufacturing has been hindered by a lack of research into…
Rob Patro, Siddhant Bharti, Prajwal Singhania, Rakrish Dhakal + 2 more
The FASTQ file format is the lingua franca of primary data distribution and processing across most of bioinformatics. Over time, the compression, storage, transmission, and decompression of gzip compressed fastq.gz files has become a substantial scalability bottleneck in the modern world of fast and massively parallel…
Drew E. Winters
Studying flexible, adaptive transitions between cognitive tasks and serial-parallel processing under changing task demands has been a central focus for understanding human cognition. Advances in neuroimaging analysis have improved the ability to link cognition with brain function, providing a foundation for developing…
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Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…
Noam Teyssier, Alexander Dobin
Single-cell genomics is rapidly scaling toward billion-cell atlases, but computational analysis has become a critical bottleneck. Processing multiplexed datasets with existing tools requires substantial computational resources and runtime that become prohibitive at scale. Here we present cyto, an ultra highthroughput…
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This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
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Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
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Background: Pharmaceutical batch production faces significant scheduling challenges due to operational uncertainties including equipment failures, yield variability, and demand fluctuations. While scheduling heuristics are widely used in practice, their comparative performance under varying uncertainty conditions…