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Biological signals, such as electroencephalograms (EEGs) and electrocardiograms (ECGs), play a pivotal role in numerous clinical practices, such as diagnosing brain and cardiac arrhythmic diseases. Existing methods for biosignal…

Machine Learning · Computer Science 2025-03-26 Jian Qian , Teck Lun Goh , Bingyu Xie , Chengyao Zhu , Biao Wan , Yawen Guan , Rachel Ding Chen , Patrick Yin Chiang

One primary goal of human microbiome studies is to predict host traits based on human microbiota. However, microbial community sequencing data present significant challenges to the development of statistical methods. In particular, the…

Methodology · Statistics 2017-10-10 Tao Wang , Can Yang , Hongyu Zhao

The preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide the first deep investigation of the predictive potential of machine…

Machine Learning · Statistics 2024-02-20 Rosa Aghdam , Xudong Tang , Shan Shan , Richard Lankau , Claudia Solís-Lemus

The identification of reproducible biological patterns from high-dimensional data is a bottleneck for understanding the biology of complex illnesses such as schizophrenia. To address this, we developed a biologically informed, multi-stage…

Quantitative Methods · Quantitative Biology 2017-12-04 Junfang Chen , Emanuel Schwarz

Fluctuating environments pose tremendous challenges to bacterial populations. It is observed in numerous bacterial species that individual cells can stochastically switch among multiple phenotypes for the population to survive in rapidly…

Molecular Networks · Quantitative Biology 2015-01-20 Chen Jia , Min-Ping Qian , Yu Kang , Da-Quan Jiang

Significant differences in protein structures hinder the generalization of existing drug-target interaction (DTI) models, which often rely heavily on pre-learned binding principles or detailed annotations. In contrast, BioBridge designs an…

Machine Learning · Computer Science 2025-03-28 Xiaoqing Lian , Jie Zhu , Tianxu Lv , Shiyun Nie , Hang Fan , Guosheng Wu , Yunjun Ge , Lihua Li , Xiangxiang Zeng , Xiang Pan

Accurately predicting chronological age from DNA methylation patterns is crucial for advancing biological age estimation. However, this task is made challenging by Epigenetic Correlation Drift (ECD) and Heterogeneity Among CpGs (HAC), which…

Genomics · Quantitative Biology 2025-01-07 Zipeng Wu , Daniel Herring , Fabian Spill , James Andrews

In meta-learning an agent extracts knowledge from observed tasks, aiming to facilitate learning of novel future tasks. Under the assumption that future tasks are 'related' to previous tasks, the accumulated knowledge should be learned in a…

Machine Learning · Statistics 2019-05-21 Ron Amit , Ron Meir

Classification of malware families is crucial for a comprehensive understanding of how they can infect devices, computers, or systems. Thus, malware identification enables security researchers and incident responders to take precautions…

Cryptography and Security · Computer Science 2022-06-23 Ferhat Demirkıran , Aykut Çayır , Uğur Ünal , Hasan Dağ

Inferring dependencies between complex biological traits while accounting for evolutionary relationships between specimens is of great scientific interest yet remains infeasible when trait and specimen counts grow large. The…

There is a growing awareness of the important roles that microbial communities play in complex biological processes. Modern investigation of these often uses next generation sequencing of metagenomic samples to determine community…

Applications · Statistics 2018-01-25 Adrian Dobra , Camilo Valdes , Dragana Ajdic , Bertrand Clarke , Jennifer Clarke

Identification of antimicrobial peptides is an important and necessary issue in today's era. Antimicrobial peptides are essential as an alternative to antibiotics for biomedical applications and many other practical applications. These…

Machine Learning · Computer Science 2025-12-17 Reyhaneh Keshavarzpour , Eghbal Mansoori

Antimicrobial stewardship (AMS) is critical in pediatric intensive care units (PICUs), where diagnostic uncertainty often drives broad-spectrum antibiotic use, increasing antimicrobial resistance and potential long-term harms. Machine…

Machine Learning · Computer Science 2026-05-22 Niklas Raehse , Luregn J. Schlapbach , Daphné Chopard

Modern biomedical data mining requires feature selection methods that can (1) be applied to large scale feature spaces (e.g. `omics' data), (2) function in noisy problems, (3) detect complex patterns of association (e.g. gene-gene…

Machine Learning · Computer Science 2018-04-04 Ryan J. Urbanowicz , Randal S. Olson , Peter Schmitt , Melissa Meeker , Jason H. Moore

Developing reliable mechanisms for continuous local learning is a central challenge faced by biological and artificial systems. Yet, how the environmental factors and structural constraints on the learning network influence the optimal…

Neurons and Cognition · Quantitative Biology 2024-03-21 Emmanouil Giannakakis , Sina Khajehabdollahi , Anna Levina

The family of f-divergences is ubiquitously applied to generative modeling in order to adapt the distribution of the model to that of the data. Well-definedness of f-divergences, however, requires the distributions of the data and model to…

Machine Learning · Statistics 2019-06-04 Akash Srivastava , Kristjan Greenewald , Farzaneh Mirzazadeh

Meta-learning, i.e., "learning to learn", is a promising approach to enable efficient BCI classifier training with limited amounts of data. It can effectively use collections of in some way similar classification tasks, with rapid…

Machine Learning · Computer Science 2025-01-22 Daniil A. Berdyshev , Artem M. Grachev , Sergei L. Shishkin , Bogdan L. Kozyrskiy

Human associated microbial communities exert tremendous influence over human health and disease. With modern metagenomic sequencing methods it is possible to follow the relative abundance of microbes in a community over time. These…

Quantitative Methods · Quantitative Biology 2015-06-18 Charles K. Fisher , Pankaj Mehta

Large language models have shown strong performance on broad-domain knowledge and reasoning benchmarks, but it remains unclear how well language models handle specialized animal-related knowledge under a unified closed-book evaluation…

Biological age, which may be older or younger than chronological age due to factors such as genetic predisposition, environmental exposures, serves as a meaningful biomarker of aging processes and can inform risk stratification, treatment…

Genomics · Quantitative Biology 2025-11-11 Shuyue Jiang , Wenjing Ma , Shaojun Yu , Chang Su , Runze Yan , Jiaying Lu