AI Medical Compendium Journal:
Statistical applications in genetics and molecular biology

Showing 1 to 5 of 5 articles

A CNN-CBAM-BIGRU model for protein function prediction.

Statistical applications in genetics and molecular biology
Understanding a protein's function based solely on its amino acid sequence is a crucial but intricate task in bioinformatics. Traditionally, this challenge has proven difficult. However, recent years have witnessed the rise of deep learning as a powe...

A novel hybrid CNN and BiGRU-Attention based deep learning model for protein function prediction.

Statistical applications in genetics and molecular biology
Proteins are the building blocks of all living things. Protein function must be ascertained if the molecular mechanism of life is to be understood. While CNN is good at capturing short-term relationships, GRU and LSTM can capture long-term dependenci...

Use of SVM-based ensemble feature selection method for gene expression data analysis.

Statistical applications in genetics and molecular biology
Gene selection is one of the key steps for gene expression data analysis. An SVM-based ensemble feature selection method is proposed in this paper. Firstly, the method builds many subsets by using Monte Carlo sampling. Secondly, ranking all the featu...

Challenges for machine learning in RNA-protein interaction prediction.

Statistical applications in genetics and molecular biology
RNA-protein interactions have long being recognised as crucial regulators of gene expression. Recently, the development of scalable experimental techniques to measure these interactions has revolutionised the field, leading to the production of large...

Finding causative genes from high-dimensional data: an appraisal of statistical and machine learning approaches.

Statistical applications in genetics and molecular biology
Modern biological experiments often involve high-dimensional data with thousands or more variables. A challenging problem is to identify the key variables that are related to a specific disease. Confounding this task is the vast number of statistical...