Computational Intelligence Methods for Bioinformatics and Biostatistics
17th International Meeting, CIBB 2021, Virtual Event, November 15–17, 2021, Revised Selected Papers
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Article
Open AccessClinical Feature Ranking Based on Ensemble Machine Learning Reveals Top Survival Factors for Glioblastoma Multiforme
Glioblastoma multiforme (GM) is a malignant tumor of the central nervous system considered to be highly aggressive and often carrying a terrible survival prognosis. An accurate prognosis is therefore pivotal f...
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Article
Open AccessSignature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma
Neuroblastoma is a childhood neurological tumor which affects hundreds of thousands of children worldwide, and information about its prognosis can be pivotal for patients, their families, and clinicians. One o...
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Article
Open AccessTen simple rules for providing bioinformatics support within a hospital
Bioinformatics has become a key aspect of the biomedical research programmes of many hospitals’ scientific centres, and the establishment of bioinformatics facilities within hospitals has become a common pract...
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Article
Open AccessThe Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification
Binary classification is a common task for which machine learning and computational statistics are used, and the area under the receiver operating characteristic curve (ROC AUC) has become the common standard ...
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Article
Open AccessTowards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning
Cancer is one of the leading causes of death worldwide and can be caused by environmental aspects (for example, exposure to asbestos), by human behavior (such as smoking), or by genetic factors. To understand ...
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Protocol
geneExpressionFromGEO: An R Package to Facilitate Data Reading from Gene Expression Omnibus (GEO)
Gene expression profiling is a useful way to measure the activity of genes in molecular biology and, because of its effectiveness, researchers have released thousands of gene expression datasets publicly in on...
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Book and Conference Proceedings
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Article
Open AccessThe Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation
Evaluating binary classifications is a pivotal task in statistics and machine learning, because it can influence decisions in multiple areas, including for example prognosis or therapies of patients in critica...
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Article
Open AccessData analytics and clinical feature ranking of medical records of patients with sepsis
Sepsis is a life-threatening clinical condition that happens when the patient’s body has an excessive reaction to an infection, and should be treated in one hour. Due to the urgency of sepsis, doctors and phys...
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Protocol
Brief Survey on Machine Learning in Epistasis
In biology, the term “epistasis” indicates the effect of the interaction of a gene with another gene. A gene can interact with an independently sorted gene, located far away on the chromosome or on an entirely...
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Protocol
Siamese Neural Networks: An Overview
Similarity has always been a key aspect in computer science and statistics. Any time two element vectors are compared, many different similarity approaches can be used, depending on the final goal of the compa...
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Article
Open AccessSurvival prediction of patients with sepsis from age, sex, and septic episode number alone
Sepsis is a life-threatening condition caused by an exaggerated reaction of the body to an infection, that leads to organ failure or even death. Since sepsis can kill a patient even in just one hour, survival ...
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Article
Open AccessMachine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone
Cardiovascular diseases kill approximately 17 million people globally every year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) occurs when the heart cannot pump enou...
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Article
Open AccessThe advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
To evaluate binary classifications and their confusion matrices, scientific researchers can employ several statistical rates, accordingly to the goal of the experiment they are investigating. Despite being a c...
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Article
Open AccessTen quick tips for machine learning in computational biology
Machine learning has become a pivotal tool for many projects in computational biology, bioinformatics, and health informatics. Nevertheless, beginners and biomedical researchers often do not have enough experi...
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Article
Open AccessGenome Informatics 2016
A report on the Genome Informatics conference, held at the Wellcome Genome Campus Conference Centre, Hinxton, United Kingdom, 19–22 September 2016.
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Chapter and Conference Paper
Validation Pipeline for Computational Prediction of Genomics Annotations
Controlled biomolecular annotations are key concepts in computational genomics and proteomics, since they can describe the functional features of genes and their products in both a simple and computational way...
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Article
Open AccessComputational algorithms to predict Gene Ontology annotations
Gene function annotations, which are associations between a gene and a term of a controlled vocabulary describing gene functional features, are of paramount importance in modern biology. Datasets of these anno...
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Chapter and Conference Paper
Extended Spearman and Kendall Coefficients for Gene Annotation List Correlation
Gene annotations are a key concept in bioinformatics and computational methods able to predict them are a fundamental contribution to the field. Several machine learning algorithms are available in this domain...
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Chapter and Conference Paper
Weighting Scheme Methods for Enhanced Genomic Annotation Prediction
Functional genomic annotation data banks, which store the associations between genes (or a gene products) and terms of controlled vocabularies describing their features, are paramount in computational biology....
