Intro
Acknowledgements
Contents
1: Setting Up a Bio-AFM to Study Protein Misfolding in Neurodegenerative Diseases
1.1 Introduction
1.2 Methods
1.2.1 Preparing and Mounting the Sample
1.2.2 Setting Up the AFM Spectroscope
1.2.3 Aligning, Mirror Adjustment, Automatic Approach, Calibrating
1.2.4 Choosing the Experiment-Setting Force Spectroscopy Parameters
1.2.5 Summary
References
2: Structural Connectivity Changes After Fornix Transection in Macaques Using Probabilistic Diffusion Tractography
2.1 Introduction
2.2 Methods
2.2.1 Subjects

2.2.2 Experimental Design and Rationale
2.2.3 Imaging Data Acquisition
2.2.4 Regions of Interest
2.2.5 Data Pre-processing
2.2.6 Probabilistic Tractography
2.2.7 Statistical Analysis
2.2.8 Fornix Transection
2.3 Results
2.4 Discussion
References
3: Detection and Quantification of Exhaled Breath Condensate and Dyspnea Correlation in Stable COPD: A Proof-of-Concept Study
3.1 Introduction
3.2 Material and Methods
3.2.1 Subjects
3.2.2 Ethics
3.2.3 Setting
3.2.4 Procedure
3.2.5 Outcome Measurements
3.2.5.1 Dyspnea Assessment

3.2.5.2 Exhaled Breath Condensate Analysis
3.2.5.3 Other Recorded Tests
3.3 Statistical Analysis
3.4 Results
3.5 Discussion
References
4: Protein Structure Prediction for Disease-Related Insertions/Deletions in Presenilin 1 Gene
4.1 Introduction
4.2 Related Work
4.3 Data Collection
4.4 Methods
4.5 Results
4.6 Conclusion
References
5: An Updated Evolutionary and Structural Study of TBK1 Reveals Highly Conserved Motifs as Potential Pharmacological Targets in Neurodegenerative Diseases
5.1 Introduction
5.2 Methods

5.2.1 Dataset Collection and Filtering
5.2.2 Multiple Sequence Alignment, Conserved Motifs, and Phylogenetic Analysis
5.2.3 Single Nucleotide Polymorphisms, Variants, and Mutation Analysis
5.2.4 Structural Analysis
5.3 Results
5.3.1 Dataset
5.3.2 Multiple Sequence Alignment and Conserved Motifs
5.3.3 Phylogenetic Analysis
5.3.4 Single Nucleotide Polymorphisms, Variants, and Mutation Analysis
5.3.5 Structural Analysis
5.4 Discussion
References

6: Semantic and Population Analysis of the Genetic Targets Related to COVID-19 and Its Association with Genes and Diseases
6.1 Introduction
6.2 Methods
6.2.1 Dataset Collection and Filtering
6.2.2 COVID-19-Related SNPs
6.2.3 Data Mining and Semantics Analysis
6.2.4 Population Analysis
6.3 Results
6.3.1 COVID-19-Related Key Terms and SNPs
6.3.2 Genomic Grammar
6.3.3 Disease Ontologies
6.3.4 Population Analysis
6.4 Discussion
References