AIMC Topic: Machine Learning

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Systematic selection of chemical fingerprint features improves the Gibbs energy prediction of biochemical reactions.

Bioinformatics (Oxford, England)
MOTIVATION: Accurate and wide-ranging prediction of thermodynamic parameters for biochemical reactions can facilitate deeper insights into the workings and the design of metabolic systems.

Fast honey classification using infrared spectrum and machine learning.

Mathematical biosciences and engineering : MBE
Honey has been one previous natural food in human history. However, as the supply cannot satisfy the market demand, many incidents of adulterated and fraudulent honey have been reported. In Taiwan, some common adulterated honey and fraudulent honey i...

Artificial intelligence in drug combination therapy.

Briefings in bioinformatics
Currently, the development of medicines for complex diseases requires the development of combination drug therapies. It is necessary because in many cases, one drug cannot target all necessary points of intervention. For example, in cancer therapy, a...

Drug knowledge bases and their applications in biomedical informatics research.

Briefings in bioinformatics
Recent advances in biomedical research have generated a large volume of drug-related data. To effectively handle this flood of data, many initiatives have been taken to help researchers make good use of them. As the results of these initiatives, many...

BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches.

Briefings in bioinformatics
With the avalanche of biological sequences generated in the post-genomic age, one of the most challenging problems is how to computationally analyze their structures and functions. Machine learning techniques are playing key roles in this field. Typi...

Representation transfer for differentially private drug sensitivity prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Human genomic datasets often contain sensitive information that limits use and sharing of the data. In particular, simple anonymization strategies fail to provide sufficient level of protection for genomic data, because the data are inher...

ConDo: protein domain boundary prediction using coevolutionary information.

Bioinformatics (Oxford, England)
MOTIVATION: Domain boundary prediction is one of the most important problems in the study of protein structure and function. Many sequence-based domain boundary prediction methods are either template-based or machine learning (ML) based. ML-based met...

GUESS: projecting machine learning scores to well-calibrated probability estimates for clinical decision-making.

Bioinformatics (Oxford, England)
MOTIVATION: Clinical decision support systems have been applied in numerous fields, ranging from cancer survival toward drug resistance prediction. Nevertheless, clinical decision support systems typically have a caveat: many of them are perceived as...