AI Medical Compendium Journal:
Functional & integrative genomics

Showing 1 to 8 of 8 articles

Integrated muti-omics data and machine learning reveal CD151 as a key biomarker inducing chemoresistance in metabolic syndrome-related early-onset left-sided colorectal cancer.

Functional & integrative genomics
Emerging evidence has suggested a potential pathological association between early-onset left-sided colorectal cancer (EOLCC) and metabolic syndrome (MetS). However, the underlying genetic and molecular mechanisms remain insufficiently elucidated. Th...

Precise genome editing process and its applications in plants driven by AI.

Functional & integrative genomics
Genome editing technologies have emerged as the keystone of biotechnological research, enabling precise gene modification. The field has evolved rapidly through revolutionary advancements, transitioning from early explorations to the breakthrough of ...

A review on advancements in feature selection and feature extraction for high-dimensional NGS data analysis.

Functional & integrative genomics
Recent advancements in biomedical technologies and the proliferation of high-dimensional Next Generation Sequencing (NGS) datasets have led to significant growth in the bulk and density of data. The NGS high-dimensional data, characterized by a large...

The impact and future of artificial intelligence in medical genetics and molecular medicine: an ongoing revolution.

Functional & integrative genomics
Artificial intelligence (AI) platforms have emerged as pivotal tools in genetics and molecular medicine, as in many other fields. The growth in patient data, identification of new diseases and phenotypes, discovery of new intracellular pathways, avai...

Integrated multi-omics analysis and machine learning to refine molecular subtypes, prognosis, and immunotherapy in lung adenocarcinoma.

Functional & integrative genomics
Lung adenocarcinoma (LUAD) has a malignant characteristic that is highly aggressive and prone to metastasis. There is still a lack of suitable biomarkers to facilitate the refinement of precision-based therapeutic regimens. We used a combination of 1...

Optimised stacked machine learning algorithms for genomics and genetics disorder detection in the healthcare industry.

Functional & integrative genomics
With recent advances in precision medicine and healthcare computing, there is an enormous demand for developing machine learning algorithms in genomics to enhance the rapid analysis of disease disorders. Technological advancement in genomics and imag...

A scoping review on deep learning for next-generation RNA-Seq. data analysis.

Functional & integrative genomics
In the last decade, transcriptome research adopting next-generation sequencing (NGS) technologies has gathered incredible momentum amongst functional genomics scientists, particularly amongst clinical/biomedical research groups. The progressive enfol...

RDDSVM: accurate prediction of A-to-I RNA editing sites from sequence using support vector machines.

Functional & integrative genomics
Adenosine to inosine (A-to-I) editing in RNA is involved in various biological processes like gene expression, alternative splicing, and mRNA degradation associated with carcinogenesis and various human diseases. Therefore, accurate identification of...