Genome interpretation using in silico predictors of variant impact
Estimating the effects of variants found in disease driver genes opens the door to
personalized therapeutic opportunities. Clinical associations and laboratory experiments …
personalized therapeutic opportunities. Clinical associations and laboratory experiments …
[HTML][HTML] A systematic review on machine learning approaches in the diagnosis and prognosis of rare genetic diseases
P Roman-Naranjo, AM Parra-Perez… - Journal of biomedical …, 2023 - Elsevier
Background The diagnosis of rare genetic diseases is often challenging due to the
complexity of the genetic underpinnings of these conditions and the limited availability of …
complexity of the genetic underpinnings of these conditions and the limited availability of …
Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks
M Nourbakhsh, K Degn, A Saksager… - Briefings in …, 2024 - academic.oup.com
The vast amount of available sequencing data allows the scientific community to explore
different genetic alterations that may drive cancer or favor cancer progression. Software …
different genetic alterations that may drive cancer or favor cancer progression. Software …
Evolutionary Action–Machine Learning Model Identifies Candidate Genes Associated With Early‐Onset Coronary Artery Disease
D Shapiro, K Lee, J Asmussen… - Journal of the …, 2023 - Am Heart Assoc
Background Coronary artery disease is a primary cause of death around the world, with both
genetic and environmental risk factors. Although genome‐wide association studies have …
genetic and environmental risk factors. Although genome‐wide association studies have …
[HTML][HTML] Advances in computational methods for identifying cancer driver genes
Y Wang, B Zhou, J Ru, X Meng, Y Wang… - Mathematical …, 2023 - aimspress.com
Cancer driver genes (CDGs) are crucial in cancer prevention, diagnosis and treatment. This
study employed computational methods for identifying CDGs, categorizing them into four …
study employed computational methods for identifying CDGs, categorizing them into four …
A systematic review on machine learning approaches in the diagnosis and prognosis of rare genetic diseases
PR Naranjo Varela, AM Parra Pérez… - 2023 - digibug.ugr.es
Background: The diagnosis of rare genetic diseases is often challenging due to the
complexity of the genetic underpinnings of these conditions and the limited availability of …
complexity of the genetic underpinnings of these conditions and the limited availability of …
A systematic review on machine learning approaches in the diagnosis of rare genetic diseases
P Roman-Naranjo, AM Parra-Perez… - medRxiv, 2023 - medrxiv.org
Background The diagnosis of rare genetic diseases is often challenging due to the
complexity of the genetic underpinnings of these conditions and the limited availability of …
complexity of the genetic underpinnings of these conditions and the limited availability of …
IMRDriver: coding and non-coding cancer driver genes identification based on network propagation
S Wang, XT Huang, KHK Chan… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
In cancer genomics, the identification of Cancer Driver Genes (CDGs) is a major scientific
interest. CDGs can be identified by numerous methods, however the false positive rate still …
interest. CDGs can be identified by numerous methods, however the false positive rate still …
Hybrid Prediction Model for Mechanical Properties of Low Alloy Steel Based on SVR-MLP
C Song - International Workshop on New Approaches for …, 2023 - Springer
As research into alloyed materials continues to advance there are different types of low-alloy
steel with different chemical compositions and organisations, so there is a need for more …
steel with different chemical compositions and organisations, so there is a need for more …