AIMC Topic: Software

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PhysioEx: a new Python library for explainable sleep staging through deep learning.

Physiological measurement
Sleep staging is a crucial task in clinical and research contexts for diagnosing and understanding sleep disorders. This work introduces PhysioEx (Physiological Signal Explainer), a Python library designed to support the analysis of sleep stages usin...

A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors.

Sensors (Basel, Switzerland)
Accurate air pollution monitoring is critical to understand and mitigate the impacts of air pollution on human health and ecosystems. Due to the limited number and geographical coverage of advanced, highly accurate sensors monitoring air pollutants, ...

GNOme, an ontology for glycan naming and subsumption.

Analytical and bioanalytical chemistry
While GlyTouCan provides stable identifiers for referencing glycan structures, they are not organized semantically. GNOme, a glycan naming and subsumption ontology and a member of the OBOFoundry, organizes GlyTouCan accessions for automated reasoning...

HybProm: An attention-assisted hybrid CNN-BiLSTM model for the interpretable prediction of DNA promoter.

Methods (San Diego, Calif.)
Promoter prediction is essential for analyzing gene structures, understanding regulatory networks, transcription mechanisms, and precisely controlling gene expression. Recently, computational and deep learning methods for promoter prediction have gai...

Machine learning models for segmentation and classification of cyanobacterial cells.

Photosynthesis research
Timelapse microscopy has recently been employed to study the metabolism and physiology of cyanobacteria at the single-cell level. However, the identification of individual cells in brightfield images remains a significant challenge. Traditional inten...

Machine Learning-Based Bioactivity Classification of Natural Products Using LC-MS/MS Metabolomics.

Journal of natural products
The rediscovery of known drug classes represents a major challenge in natural products drug discovery. Compound rediscovery inhibits the ability of researchers to explore novel natural products and wastes significant amounts of time and resources. Th...

Med-ImageTools: An open-source Python package for robust data processing pipelines and curating medical imaging data.

F1000Research
BACKGROUND: Machine learning and AI promise to revolutionize the way we leverage medical imaging data for improving care but require large datasets to train computational models that can be implemented in clinical practice. However, processing large ...

Towards robotic Laboratory Automation Plug & Play: LAPP reference implementation with the TIAGo mobile manipulator.

SLAS technology
Laboratory automation with mobile manipulators presents a promising avenue for enhancing efficiency and reducing the dependency on human activity in laboratory workflows. To achieve seamless integration, the Laboratory Automation Plag & Play concept ...

DeepPrep: an accelerated, scalable and robust pipeline for neuroimaging preprocessing empowered by deep learning.

Nature methods
Neuroimaging has entered the era of big data. However, the advancement of preprocessing pipelines falls behind the rapid expansion of data volume, causing substantial computational challenges. Here we present DeepPrep, a pipeline empowered by deep le...

FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images.

PloS one
The extracellular matrix (ECM) is a complex network of biomolecules that plays an integral role in the structure, processes, and signaling mechanisms of cells and tissues. Identifying and quantifying changes in these matrix components provides insigh...