Incorporating machine learning into established bioinformatics frameworks
The exponential growth of biomedical data in recent years has urged the application of
numerous machine learning techniques to address emerging problems in biology and …
numerous machine learning techniques to address emerging problems in biology and …
The impact of artificial intelligence in the odyssey of rare diseases
Emerging machine learning (ML) technologies have the potential to significantly improve the
research and treatment of rare diseases, which constitute a vast set of diseases that affect a …
research and treatment of rare diseases, which constitute a vast set of diseases that affect a …
Drug repurposing for COVID-19 using machine learning and mechanistic models of signal transduction circuits related to SARS-CoV-2 infection
Drug repurposing is a convenient alternative when the need for new drugs in an unexpected
medical scenario is urgent, as is the case of emerging pathogens. In recent years …
medical scenario is urgent, as is the case of emerging pathogens. In recent years …
A comprehensive review of computational cell cycle models in guiding cancer treatment strategies
C Ma, E Gurkan-Cavusoglu - NPJ Systems Biology and Applications, 2024 - nature.com
This article reviews the current knowledge and recent advancements in computational
modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms …
modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms …
A comprehensive database for integrated analysis of omics data in autoimmune diseases
Background Autoimmune diseases are heterogeneous pathologies with difficult diagnosis
and few therapeutic options. In the last decade, several omics studies have provided …
and few therapeutic options. In the last decade, several omics studies have provided …
Systematic review: drug repositioning for congenital disorders of glycosylation (CDG)
S Brasil, M Allocca, SCM Magrinho, I Santos… - International Journal of …, 2022 - mdpi.com
Advances in research have boosted therapy development for congenital disorders of
glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid …
glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid …
Artificial intelligence in epigenetic studies: shedding light on rare diseases
S Brasil, CJ Neves, T Rijoff, M Falcão… - Frontiers in Molecular …, 2021 - frontiersin.org
More than 7,000 rare diseases (RDs) exist worldwide, affecting approximately 350 million
people, out of which only 5% have treatment. The development of novel genome …
people, out of which only 5% have treatment. The development of novel genome …
Mechanistic modeling of the SARS-CoV-2 disease map
Here we present a web interface that implements a comprehensive mechanistic model of the
SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling …
SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling …
Using mechanistic models for the clinical interpretation of complex genomic variation
The sustained generation of genomic data in the last decade has increased the knowledge
on the causal mutations of a large number of diseases, especially for highly penetrant …
on the causal mutations of a large number of diseases, especially for highly penetrant …
AI-Driven Drug Discovery for Rare Diseases
A Gangwal, A Lavecchia - Journal of Chemical Information and …, 2024 - ACS Publications
Rare diseases (RDs), affecting 300 million people globally, present a daunting public health
challenge characterized by complexity, limited treatment options, and diagnostic hurdles …
challenge characterized by complexity, limited treatment options, and diagnostic hurdles …