Unraveling Genotype-Phenotype Relations: Cutting-edge Insights
Table of Contents
- Introduction
- Background and Objectives
- 2.1 Understanding Biomedical Data
- 2.2 Challenges in Data Navigation
- Exploring Biomedical Data Interfaces
- 3.1 Traditional Databases
- 3.2 Visual Analytics Approaches
- Interactive Visual Analytics Tools
- 4.1 Importance in Biomedical Research
- 4.2 Role in Formulating Hypotheses
- Barbara Morrell's Research
- 5.1 Insights into Future Tools
- 5.2 Supporting Explanatory Analysis
- Collaborations and Initiatives
- 6.1 The Monarch Initiative
- 6.2 Functional Genomics Visualization
- Research Question and Aims
- 7.1 Defining the Research Question
- 7.2 Specific Aims of the Project
- Project Plan
- 8.1 Designing Visualization Prototypes
- 8.2 Developing Interactive Prototypes
- 8.3 Usability Evaluation of Prototypes
- Evaluation Methods
- 9.1 Heuristic Evaluation
- 9.2 Think Aloud Protocol
- 9.3 System Usability Scale
- Expected Outcomes
- 10.1 Qualitative Analysis Report
- 10.2 Case Study on User Interaction
- Proposed Timeline
- 11.1 Aim 1: Initial Mock-ups and Scenarios
- 11.2 Aim 2: Prototype Development
- 11.3 Aim 3: Usability Evaluation
- Acknowledgments and Conclusion
Introduction
👋 Welcome, everyone! Can you hear me okay? It's my pleasure to introduce to you your speaker for this morning, Eric Sederdal. Eric, a Master's student in D mice, received his bachelor's degree in biology from the University of Oregon in 1992. Currently, he's delving into the intriguing realm of how an interactive visual analytics tool can assist biomedical scientists in investigating genotype-phenotype relationships.
Background and Objectives
2.1 Understanding Biomedical Data
In the vast landscape of biomedical research, comprehending the intricate relationships between genotypes and phenotypes is fundamental. However, navigating through the plethora of data poses a significant challenge.
2.2 Challenges in Data Navigation
Traditional databases, while rich in genetic and phenotypic information, often Present obstacles in accessibility and interpretation. Visual analytics approaches offer promise in illuminating these complex datasets.
Exploring Biomedical Data Interfaces
3.1 Traditional Databases
Mono organism databases have long been invaluable resources, yet their text-based interfaces can hinder efficient data retrieval and synthesis.
3.2 Visual Analytics Approaches
Recent developments in visualization widgets, exemplified by initiatives like the Monarch Initiative, demonstrate the potential of dynamic, interactive elements in data exploration and understanding.
Interactive Visual Analytics Tools
4.1 Importance in Biomedical Research
The significance of interactive visual analytics tools lies in their ability to facilitate hypothesis generation and narrative synthesis, crucial for advancing our understanding of human diseases.
4.2 Role in Formulating Hypotheses
By enabling users to traverse complex datasets and uncover Hidden connections, these tools empower researchers to develop insightful hypotheses regarding genotype-phenotype associations.
Barbara Morrell's Research
5.1 Insights into Future Tools
Morrell's exploration into future bioinformatics tools emphasizes the transition from exploratory to explanatory analysis, thereby fostering deeper insights into biological systems.
5.2 Supporting Explanatory Analysis
Identifying key features that promote explanatory analysis is pivotal in enhancing the usability and effectiveness of visual analytics tools.
Collaborations and Initiatives
6.1 The Monarch Initiative
Collaborative efforts, such as the Monarch Initiative, aim to harness semantic tools for navigating complex biomedical data, fostering interdisciplinary research and innovation.
6.2 Functional Genomics Visualization
Initiatives focused on functional genomics visualization, like the HitWalker tool, underscore the importance of integrating genomic information to prioritize sequence variants in diseases like cancer.
Research Question and Aims
7.1 Defining the Research Question
The primary inquiry revolves around how interactive visual analytics tools can aid biomedical scientists in unraveling genotype-phenotype relationships, paving the way for Novel insights and discoveries.
7.2 Specific Aims of the Project
The project entails designing and evaluating interactive prototypes to elucidate the usability and effectiveness of these tools in facilitating explanatory data analysis.
Project Plan
8.1 Designing Visualization Prototypes
Initial mock-ups and Scenario development will lay the groundwork for creating user-centric interactive prototypes tailored to the specific needs of biomedical researchers.
8.2 Developing Interactive Prototypes
Utilizing D3 and other technologies, high-fidelity prototypes will be constructed to simulate real-world data exploration scenarios, incorporating feedback from user groups.
8.3 Usability Evaluation of Prototypes
A comprehensive usability evaluation, comprising heuristic inspection, think aloud protocol, and system usability scale, will assess the effectiveness and user satisfaction of the prototypes.
Evaluation Methods
9.1 Heuristic Evaluation
Drawing upon Nielsen's heuristics, experts will assess the prototypes' adherence to established interaction design principles, ensuring intuitive navigation and information presentation.
9.2 Think Aloud Protocol
User groups will engage in think aloud Sessions to articulate their thought processes while interacting with the prototypes, providing valuable insights into usability and functionality.
9.3 System Usability Scale
The system usability scale will quantify users' subjective assessments of usability, complemented by qualitative interviews to elucidate their experiences and preferences.
Expected Outcomes
10.1 Qualitative Analysis Report
A comprehensive report detailing the qualitative analysis of the prototypes, along with a case study highlighting user interactions, will provide valuable insights for future interface development.
10.2 Case Study on User Interaction
In-depth examination of user interactions will shed light on usability challenges and preferences, informing iterative improvements and guiding future research endeavors.
Proposed Timeline
11.1 Aim 1: Initial Mock-ups and Scenarios
Over the next month and a half, initial mock-ups and user scenarios will be developed, setting the stage for prototype design and evaluation.
11.2 Aim 2: Prototype Development
Prototypes will be developed, incorporating feedback from stakeholders and user groups, with a focus on technical feasibility and user-centric design.
11.3 Aim 3: Usability Evaluation
Usability evaluation will span until the end of June, encompassing heuristic inspection, think aloud sessions, and system usability assessment to gauge the prototypes' effectiveness and user satisfaction.
Acknowledgments and Conclusion
In conclusion, this project endeavors to advance the field of biomedical informatics by developing interactive visual analytics tools that empower researchers to navigate complex datasets and derive Meaningful insights into genotype-phenotype relationships. Special thanks to all collaborators and mentors for their invaluable support and guidance throughout this endeavor.
Highlights
- Interactive Visual Analytics Tools: Empowering biomedical scientists to explore genotype-phenotype relationships through intuitive and dynamic interfaces.
- Usability Evaluation: Employing heuristic evaluation, think aloud protocol