Machine learning for genetic prediction of psychiatric disorders: a systematic review
Abstract Machine learning methods have been employed to make predictions in psychiatry
from genotypes, with the potential to bring improved prediction of outcomes in psychiatric …
from genotypes, with the potential to bring improved prediction of outcomes in psychiatric …
Detecting polygenic evolution: problems, pitfalls, and promises
M Wellenreuther, B Hansson - TRENDS in Genetics, 2016 - cell.com
Unraveling the genetic basis of organismal form and function remains one of the major goals
of evolutionary biology. Theory has long supported a model of polygenic evolution in which …
of evolutionary biology. Theory has long supported a model of polygenic evolution in which …
A platform for experimental precision medicine: The extended BXD mouse family
The challenge of precision medicine is to model complex interactions among DNA variants,
phenotypes, development, environments, and treatments. We address this challenge by …
phenotypes, development, environments, and treatments. We address this challenge by …
[HTML][HTML] Enhancing building energy efficiency using a random forest model: A hybrid prediction approach
The building envelope considerably influences building energy consumption. To enhance
the energy efficiency of buildings, this paper proposes an approach to predict building …
the energy efficiency of buildings, this paper proposes an approach to predict building …
Genomic prediction of breeding values using a subset of SNPs identified by three machine learning methods
The analysis of large genomic data is hampered by issues such as a small number of
observations and a large number of predictive variables (commonly known as “large P small …
observations and a large number of predictive variables (commonly known as “large P small …
E3 ubiquitin ligase MAGI3 degrades c-Myc and acts as a predictor for chemotherapy response in colorectal cancer
H Wang, W Yang, Q Qin, X Yang, Y Yang, H Liu, W Lu… - Molecular cancer, 2022 - Springer
Background Recurrence and chemoresistance constitute the leading cause of death in
colorectal cancer (CRC). Thus, it is of great significance to clarify the underlying …
colorectal cancer (CRC). Thus, it is of great significance to clarify the underlying …
A machine learning model for accurate prediction of sepsis in ICU patients
D Wang, J Li, Y Sun, X Ding, X Zhang, S Liu… - Frontiers in public …, 2021 - frontiersin.org
Background: Although numerous studies are conducted every year on how to reduce the
fatality rate associated with sepsis, it is still a major challenge faced by patients, clinicians …
fatality rate associated with sepsis, it is still a major challenge faced by patients, clinicians …
A practical introduction to Random Forest for genetic association studies in ecology and evolution
MSO Brieuc, CD Waters, DP Drinan… - Molecular ecology …, 2018 - Wiley Online Library
Large genomic studies are becoming increasingly common with advances in sequencing
technology, and our ability to understand how genomic variation influences phenotypic …
technology, and our ability to understand how genomic variation influences phenotypic …
Cancer diagnosis through IsomiR expression with machine learning method
Z Liao, D Li, X Wang, L Li, Q Zou - Current Bioinformatics, 2018 - ingentaconnect.com
Background: IsomiR is an isoform of microRNA (miRNA), and its sequences vary from those
of a reference miRNA, which arose with the advencements of deep sequencing, high miRNA …
of a reference miRNA, which arose with the advencements of deep sequencing, high miRNA …
Decision trees and random forests
M Fratello, R Tagliaferri - Encyclopedia of bioinformatics and …, 2018 - books.google.com
Technological advancements of the last decades sparked an explosion in the amounts of
data acquired in several scientific fields. In particular, high-throughput technologies have …
data acquired in several scientific fields. In particular, high-throughput technologies have …