GeNeDis 2020: Computational Biology and Bioinformatics (Advances in Experimental Medicine and Biology, 1338)

✍ Scribed by Panayiotis Vlamos (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 283
• Category: Library

✦ Synopsis

The 4^th World Congress on Genetics, Geriatrics and Neurodegenerative Diseases Research (GeNeDis 2020) focuses on the latest major challenges in scientific research, new drug targets, the development of novel biomarkers, new imaging techniques, novel protocols for early diagnosis of neurodegenerative diseases, and several other scientific advances, with the aim of better, safer, and healthier aging. Computational methodologies for implementation on the discovery of biomarkers for neurodegenerative diseases are extensively discussed. This volume focuses on the sessions from the conference regarding computational biology and bioinformatics.

✦ Table of Contents

Preface
Acknowledgment
Contents
Editor Biography
Digging for Significant Genes in Microarray Expression Data Based on Systematic Sampling and Hierarchal Clustering Algorithm
1 Introduction
2 Methodology
2.1 Hierarchical Clustering Algorithm
2.2 The Systematic Sampling
3 Data Sets
3.1 Adjusted Rand Index (ARI)
4 The Proposed Algorithm (SSCH)
5 Results and Discussion
6 Conclusion
References
A DSS for Predicting Lymphoma in Primary Sjogren’s Syndrome Patients
1 Introduction
2 Materials and Methods
2.1 Data
2.2 Feature Selection
2.3 Models
3 Results
4 Web Application Implementation
5 Discussion
References
Decision Support System for Breast Cancer Detection Using Biomarker Indicators
1 Introduction
2 Materials and Methods
2.1 Breast Cancer Coimbra Dataset
2.2 Model Extraction Approach
3 Performance Assessment
3.1 Experimental Phases
3.2 Results
4 Application Design
4.1 Client Side: iOS Application
4.2 Server Side
5 Conclusions
References
Hepatocellular Carcinoma Detection Using Machine Learning Techniques
1 Introduction
2 Related Work
3 Data Preprocessing
4 Experiments and Results
5 Web Platform
6 Conclusions
References
Web-Based Decision Support System for Coronary Heart Disease Diagnosis
1 Introduction
2 Materials and Methods
2.1 Dataset Description and Data Preprocessing
2.2 Machine Learning Algorithms
2.3 Web-Based Decision Support System Development
3 Results
3.1 Models Evaluation
3.2 Web-Based Decision Support System
4 Discussion
References
A Decision Support System for the Prediction of Drug Predisposition Through Personality Traits
1 Introduction
2 Materials and Methods
2.1 Dataset
2.2 Feature Selection and Preprocessing
2.3 Classification Algorithms
3 Results
3.1 Classification
3.2 Decision Support System
4 Discussion
References
Development of a Diagnostic Tool for Balance Disorders Based on Machine Learning Techniques
1 Introduction
2 Related Work
3 Data
4 Methods
4.1 Feature Selection
4.2 Machine Learning Experiments
5 Results
5.1 Determinant Features
5.2 Evaluation Metrics
6 Conclusions
References
Systems Approaches in the Common Metabolomics in Acute Lymphoblastic Leukemia and Rhabdomyosarcoma Cells: A Computational Approach
1 Introduction
1.1 Bioinformatics and the New Advent of Systems Biology
1.2 Systems Theory and Modeling
1.3 Systems Theory and Systems Biology
2 Materials and Methods
2.1 Experimental Setup
2.2 Microarray Experimentation
2.3 Bioinformatics and Systems Analyses
2.4 Simulation
3 Results
3.1 The Ontology of the Transcriptional Profile
3.2 The Time-Dependent Evolution of Molecules
3.3 Polar Transformation of Time-Dependent Evolution
3.4 Species-Dependent Evolution of the Total System for All Time Points
4 Discussion
5 Conclusions
References
Bioinformatics Analyses of Spatial Peripheral Circadian Clock-Mediated Gene Expression of Glucocorticoid Receptor-Related Genes
1 Introduction
2 Materials and Methods
2.1 Subjects Enrolled and Study Design
2.2 Total RNA Isolation and SYBR Green Real-Time PCR
2.3 Data Analysis
2.3.1 Real-Time Data Analysis
2.3.2 Unsupervised Classifying Methodologies
2.3.3 Polynomial and Exponential Regression Analysis
2.3.4 Correlation Analysis
2.3.5 Statistical Analysis
3 Results
3.1 Statistical and Correlation Analysis
3.2 HCL Analysis
3.3 K-Means Clustering Analysis
3.4 ROC Classification
3.5 Naïve Bayes Classification
3.6 Regressions of Estimated Variables
4 Discussion
5 Conclusions
References
Machine Learning for Autistic Spectrum Disorder Risk Screening
1 Introduction
2 Past Related Work
3 Dataset
3.1 Features
3.2 Processing
3.3 Statistics
4 Algorithms
5 Results
6 Application Stack
7 Autism Spectrum Disorder Screening Application
7.1 Technical Description
7.2 Layout
8 Conclusions
References
Mobile Application for Monitoring and Preventing Cognitive Decline Through Lifestyle Intervention
1 Introduction
2 Related Work
3 Models
4 Application
4.1 Architecture
4.2 Implementation
5 Discussion
References
Virtual Reality Zoo Therapy for Alzheimer’s Disease Using Real-Time Gesture Recognition
1 Introduction
2 Related Works
2.1 Animal Therapy for Alzheimer’s Disease
2.2 Virtual Reality and Alzheimer’s Disease
2.3 Gesture Detection
3 Our Approach: Zoo Therapy System
3.1 Zoo VR
3.2 EEG Measures
3.3 Gesture Recognition System
3.4 Intelligent Agent
4 Experiments
5 Results
6 Conclusion
References
Validation of the Greek Version of Social Media Disorder Scale
1 Introduction
2 Methods
2.1 Translation Procedure
2.2 Participants and Procedures
2.3 Ethical Considerations
2.4 Measures
2.5 Statistical Analysis
3 Results
4 Discussion
References
Adiponectin and Its Effects on Acute Leukemia Cells: An Experimental and Bioinformatics Approach
1 Introduction
1.1 Adiponectin
1.2 Childhood Acute Lymphoblastic Leukemia
1.3 Adiponectin and Childhood Acute Lymphoblastic Leukemia
1.4 Scope
2 Materials and Methods
2.1 Cell Culture and Adiponectin Treatment
2.2 Microarray Experimentation
2.2.1 RNA Extraction
2.2.2 cDNA Microarrays
2.3 Data Analysis
2.3.1 Flow Cytometry Data Analysis
2.3.2 Microarray Data Analysis
3 Results
3.1 Proliferation Induced by Adiponectin
3.2 Cytotoxicity and Cell Cycle Distribution Induced by Adiponectin
3.3 Gene Expression Profiling
4 Discussion
5 Conclusions
References
Nature and Quantum-Inspired Procedures – A Short Literature Review
1 Introduction
2 Literature Review
2.1 Quantum-Inspired Procedures in the Literature
3 Conclusion and Further Work
References
Handling the Cellular Complex Systems in Alzheimer’s Disease Through a Graph Mining Approach
1 Introduction
1.1 Alzheimer’s Disease and Systems Biology
1.2 Basics to Molecular Biology
1.3 Pathway Analysis
2 Methods
3 Results and Discussion
3.1 Ensemble DEG Evaluation to Simulated Data
3.2 Application to Real Data
References
Debunking the Neuromyth of Learning Style
1 Introduction
2 Literature Review
2.1 Neuromyths
2.2 Multiple Representations
3 Methods
3.1 Participants
3.2 Procedure
4 Analysis and Findings
5 Limitations
6 Conclusions
Annex I: Visual Version
Annex II: Auditory Version
Annex III: Kinesthetic Version
Annex IV: Structured Interview
References
Expert Characteristics: Implications for Expert Systems
1 Introduction
2 Inside the Expert
2.1 Specificity and Creativity in Experts
2.2 Abilities
2.2.1 G-Factor
2.2.2 Theory of Multiple Intelligences
2.2.3 Triarchic Theory of Successful Intelligence
2.2.4 Other Theories
3 A Brief Study of Expert Memory
3.1 Expert Processing of Stimuli
4 Expert(ise) Characteristics
4.1 A Compilation of Expert Characteristics
5 Expert Characteristics and Expert Systems
6 The Contributory Expert Generalist
7 Conclusion
References
Improving the Run-Time of Space-Efficient n-Gram Data Structures Using Apache Spark
1 Introduction
2 Related Work
3 Proposed Method
3.1 Two-Level Inverted Index Example
4 Implementation
4.1 Dataset
4.2 Apache Spark Framework
5 Results
5.1 Dataset of 5 MB
5.2 Dataset of 20 MB
6 Conclusions and Future Work
References
Development of a Protein Biochip Platform for Parkinson’s Disease
1 Introduction
2 Biosensor Research and Characterization of Detection System Properties
3 Conclusions
References
The Use of Data Collection and Big Data Analysis in Neurodegenerative Disease Prevention
Fractal Dynamics in the RR Interval of Craniopharyngioma and Adrenal Tumor in Adolescence
1 Introduction
1.1 Craniopharyngiomas and Adrenal Tumors
1.2 Fractals
1.3 Scope
2 Materials and Methods
2.1 Subjects Enrolled and Study Design
2.2 Measurements and Data Collection
2.3 Data Analysis
3 Results
3.1 The Time Series
3.2 The 2D Phase Space of the Time Series
3.3 The 3D Phase Space of the Time Series
4 Discussion
4.1 Conclusions
References
Bioinformatics Approaches for Parkinson’s Disease in Clinical Practice: Data-Driven Biomarkers and Pharmacological Treatment
1 Introduction
2 Parkinson’s Disease and Related Biomarkers
3 Bioinformatics Analysis and Dynamic Network Models
4 Therapeutic Strategies in PD
References
Emerging Machine Learning Techniques for Modelling Cellular Complex Systems in Alzheimer’s Disease
1 Introduction
2 Basics of Machine Learning
3 Basics of Molecular Biology Networks
3.1 Gene Regulatory Network
3.2 Protein Interaction Networks
3.3 Metabolic Networks
3.4 Signaling Pathways
3.5 Molecular Biology Databases
4 Methods for Gene Regulatory Network Reconstruction: Related Works
4.1 Methods Based on Correlation and Mutual Information
4.2 Methods Based on Machine Learning and Regression
5 GRN Reconstruction Through Recent Machine Learning Tools
6 Discussion: Challenges and Future Prospects
References
Cognitive Enhancement Through Mathematical Problem-Solving
1 Introduction
2 Research Methodology
3 Findings
4 Conclusions
References
Cognitive Tasks of an Information System for Memory Training and Cognitive Enhancement Using Mobile Devices
1 Introduction
2 Utilization of Mobile Devices
3 Cognitive Training Information System
4 Conclusion
References
An Application for Exploring Visual Perception: A Pilot Neuroeducational Study
1 Introduction
2 Related Work
3 Explain the Application
3.1 Basic Functionality
3.2 Graphical User Interface
4 Explain the Algorithm
4.1 Scoring Method
4.2 Image Comparison
5 Obstacles to Create a Digital Version of the ROCF Test
6 Future Work
7 Conclusion
References
Gene Classification Based on Multi-Class SVMs with Systematic Sampling and Hierarchical Clustering (SSHC) Algorithm
1 Introduction
2 Methodology
2.1 The Hierarchical Clustering (SSHC) with Systematic Sampling Algorithm
2.2 Multi-Class Support Vector Machines (MCSVMs)
2.2.1 One-Against-One (OAO) Support Vector Machines
2.2.2 Directed Acyclic Graph (DAG) Support Vector Machines
2.2.3 Binary Tree (BT) Support Vector Machines
2.2.4 One-Against-All (OAA) Support Vector Machines
2.3 Evaluation Metrics
3 Microarray Expression Datasets
3.1 Adipose Tissue Macrophages (ATMs)
3.2 Adipose Tissue Macrophages (EATMs) with Metabolic Signatures
4 The Proposed SSHC-MCSVM Algorithm
5 Result and Discussion
6 Conclusion
References
Multinetwork Motor Learning as a Model for Dance in Neurorehabilitation
1 Introduction
2 Dance and Neuroplasticity: Review of Dance Elements
3 Motor Learning in the Real World
4 Motor Control Training
5 Spatial Orienting
6 Timing and Entrainment
7 Action Observation
8 Future Topics: More Than Movement Training
References
Controlling the Chimera Form in the Leaky Integrate-and-Fire Model
1 Introduction
2 The Model
2.1 Coupling Scheme of LIF Network
2.2 Modification in the Threshold Potentials
2.3 The Kuramoto Synchronization Index
3 Chimera States under Broken Connectivity
3.1 Single Chimera
3.2 Multichimera States
4 The Effects of Frequency Disorder
5 Conclusions and Open Problems
References
Qualitative Differences Between the Semi-separable and the “Almansi-Type” Stokes Stream Function Expansions in the Study of Biological Fluids
1 Introduction
2 Theoretical Background
2.1 Stokes Operators E2 and E4 in Prolate Spheroidal Coordinates: Eigenfunctions in Separable and Semiseparable Forms
2.2 The “Almansi-Type” Approach
3 Results
3.1 Connection Formula for the Eigenfunction Expansions: Reduction of the Almansi-Type Solutions to the Semiseparable Ones
3.2 The Oblate Spheroidal Case
3.3 Sample Calculations: Eigenflow Patterns
4 Discussion
References
A Multiscale Mathematical Model for Tumor Growth, Incorporating the GLUT1 Expression
1 Introduction
2 Formulation of the Problem
3 Materials and Method
4 Results and Discussion
5 Conclusions
References
Correction to: Development of a Protein Biochip Platform for Parkinson’s Disease
Index