arXiv Machine Learning
Jun 30
Friend or Foe
arXiv:2509. 00123v2 Announce Type: replace-cross Abstract: A fundamental challenge in microbial ecology is determining whether bacteria compete or cooperate in different environmental conditions.
Knowledge-Inclusive Adaptive Physics-Informed Neural Network for Microbial Interaction Modelling
arXiv:2606. 07686v1 Announce Type: cross Abstract: Physics-Informed Neural Network (PINN) is a way of including knowledge in the form of equations in Machine Learning methods.
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arXiv Machine Learning
Jul 8
Canopy: A Heterograph Foundation Model for Metabolic Engineering
arXiv:2607. 06224v1 Announce Type: new Abstract: Designing microbial strains that produce high-value chemicals at commercially viable titers remains a central challenge in metabolic engineering.
arXiv AI
Jul 24
Leveraging Biokinetic Knowledge Priors for Data-Scarce Bioprocess Modeling
arXiv:2607. 20539v1 Announce Type: cross Abstract: While deep learning has accelerated drug discovery, its impact on biomanufacturing has been considerably more limited.
arXiv Machine Learning
Jul 3
Structured Gaussian Processes for Uncertainty-Aware Classification of High-Dimensional, Small-Sampled Omics Data
arXiv:2607. 02103v1 Announce Type: cross Abstract: Classifying heterogeneous omics data remains a fundamental challenge in computational biology, particularly in high-dimensional, small-sample settings where nonlinear interactions dominate and class imbalance further complicates reliable prediction of minority phenotypes.
arXiv Machine Learning
Jun 19
Constrained hybrid modelling to predict microbial dynamics and organic matter turnover in soil systems
arXiv:2606. 20329v1 Announce Type: new Abstract: Soil microorganisms control organic matter cycling and largely determine how soil systems can cope with and mitigate climate change and environmental threats.
arXiv Machine Learning
Jun 29
Effects of relational graph modularity and depth on the learning performance of neural networks
arXiv:2507. 10005v2 Announce Type: replace Abstract: In recent years, graph-based machine learning techniques, such as reinforcement learning and graph neural networks, have garnered significant attention.
arXiv AI
Aug 11
Biologically Informed Representation Learning for Robust Cross-Center Generalization of MALDI-TOF Mass Spectrometry
arXiv:2608. 08182v1 Announce Type: cross Abstract: Machine learning models for MALDI-TOF mass spectrometry have shown considerable promise for clinical microbiology tasks such as microbial identification and antimicrobial resistance prediction.
arXiv Machine Learning
Aug 10
Beyond Attention: Signed Integrated Gradients Attribution in a BiomeGPT-Style Microbiome Transformer
arXiv:2608. 06486v1 Announce Type: new Abstract: In a feature-tokenized transformer (arXiv:2106.
arXiv AI
Jul 2
Autonomous Scientific Discovery via Iterative Meta-Reflection
arXiv:2607. 01131v1 Announce Type: cross Abstract: Autonomous scientific discovery systems offer the potential to accelerate research by automating the process of hypothesis generation and validation.
arXiv Machine Learning
Jul 1
ElemeNet: Multiscale Molecular Machine Learning with Uncertainty Quantification Across the Periodic Table
arXiv:2606. 30961v1 Announce Type: cross Abstract: Advances in deep learning architectures and representations have enabled ML-driven chemical property prediction, but state-of-the-art (SOTA) models have remained largely confined to independent codebases and lack support for diverse chemical species.
arXiv AI
Aug 3
Can Large Language Models Derive New Knowledge? A Dynamic Benchmark for Biological Knowledge Discovery
arXiv:2603. 03322v2 Announce Type: replace-cross Abstract: Recent advancements in Large Language Model (LLM) agents have demonstrated remarkable potential in automatic knowledge discovery.
arXiv AI
Jul 3
MKGR: Multimodal Knowledge-Graph Representation Learning for Cold-Start Protein-Protein Interaction Prediction
arXiv:2607. 01627v1 Announce Type: cross Abstract: Accurate protein-protein interaction (PPI) prediction is central to functional genomics, disease mechanism discovery, and drug development.