AIMC Topic: Software

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LOMETS3: integrating deep learning and profile alignment for advanced protein template recognition and function annotation.

Nucleic acids research
Deep learning techniques have significantly advanced the field of protein structure prediction. LOMETS3 (https://zhanglab.ccmb.med.umich.edu/LOMETS/) is a new generation meta-server approach to template-based protein structure prediction and function...

Performance Evaluation of Embedded Image Classification Models Using Edge Impulse for Application on Medical Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This work explores the possibility of applying edge machine learning technology in the context of portable medical image diagnostic systems. This was done by evaluating the performance of two machine learning (ML) algorithms, that are widely used on ...

A Formal Model for the FAIR4Health Information Architecture.

Studies in health technology and informatics
In the EU project FAIR4Health, a ETL pipeline for the FAIRification of structured health data as well as an agent-based, distributed query platform for the analysis of research hypotheses and the training of machine learning models were developed. Th...

Comparison of Data Classification Results for Leap Motion Recovery Gestures.

Studies in health technology and informatics
Static and dynamic gestures are frequently used in activities supporting learning, recovery healthcare, engineering, and 3D games to increase the interactivity between man and machine. The gestures are detected via hardware devices and data is proces...

Scaling multi-instance support vector machine to breast cancer detection on the BreaKHis dataset.

Bioinformatics (Oxford, England)
MOTIVATION: Breast cancer is a type of cancer that develops in breast tissues, and, after skin cancer, it is the most commonly diagnosed cancer in women in the United States. Given that an early diagnosis is imperative to prevent breast cancer progre...

MLGL-MP: a Multi-Label Graph Learning framework enhanced by pathway interdependence for Metabolic Pathway prediction.

Bioinformatics (Oxford, England)
MOTIVATION: During lead compound optimization, it is crucial to identify pathways where a drug-like compound is metabolized. Recently, machine learning-based methods have achieved inspiring progress to predict potential metabolic pathways for drug-li...

An approachable, flexible and practical machine learning workshop for biologists.

Bioinformatics (Oxford, England)
SUMMARY: The increasing prevalence and importance of machine learning in biological research have created a need for machine learning training resources tailored towards biological researchers. However, existing resources are often inaccessible, infe...

BITES: balanced individual treatment effect for survival data.

Bioinformatics (Oxford, England)
MOTIVATION: Estimating the effects of interventions on patient outcome is one of the key aspects of personalized medicine. Their inference is often challenged by the fact that the training data comprises only the outcome for the administered treatmen...

A LASSO-based approach to sample sites for phylogenetic tree search.

Bioinformatics (Oxford, England)
MOTIVATION: In recent years, full-genome sequences have become increasingly available and as a result many modern phylogenetic analyses are based on very long sequences, often with over 100 000 sites. Phylogenetic reconstructions of large-scale align...

CLIN-X: pre-trained language models and a study on cross-task transfer for concept extraction in the clinical domain.

Bioinformatics (Oxford, England)
MOTIVATION: The field of natural language processing (NLP) has recently seen a large change toward using pre-trained language models for solving almost any task. Despite showing great improvements in benchmark datasets for various tasks, these models...