Reading List

This reading list provides a curated selection of resources related to the intersection of AI, biology, knowledge graphs, and the future of scientific research. Each entry is accompanied by contextual information and categorized to enhance understanding and facilitate deeper exploration.

AI & Automation in Science

• Sakana AI Scientist Agents

  • Category: AI Agents, Scientific Automation

  • Context: Explores the development of AI scientist agents capable of autonomously conducting experiments and generating hypotheses.

  • https://sakana.ai/ai-scientist/

• AI Tools Are Spotting Errors in Research Papers: Inside a Growing Movement

  • Category: AI in Research, Error Detection

  • Context: Discusses the use of AI tools to identify errors in scientific research papers, improving accuracy and reliability.

  • https://archive.ph/RekIL

• BioAgents: Accelerating Decentralized Science with AI Agents

  • Category: AI Agents, Decentralized Science

  • Context: Discusses the use of AI agents to accelerate decentralized science, democratizing research.

  • https://www.bio.xyz/blog-posts/bioagents-pioneering-decentralized-science-with-ai-agents

Knowledge Graphs & Data Management

• The Implicitome: A Resource for Rationalizing Gene-Disease Associations

  • Category: Knowledge Graphs, Gene-Disease Relationships

  • Context: Provides data and tools for understanding gene-disease associations, aiding in knowledge graph creation.

  • https://archive.ph/jpULH

• SciGraph: The Dawn of a New Scientific Era

  • Category: Knowledge Graphs, Scientific Data

  • Context: Explores SciGraph and its potential to create a comprehensive knowledge graph of scientific information.

  • https://medium.com/id-theory/scigraph-the-dawn-of-a-new-scientific-era-d067e293c6b2

• FAIR Guiding Principles for Scientific Data Management and Stewardship

  • Category: Data Management, FAIR Principles

  • Context: Outlines the FAIR principles for managing scientific data, crucial for data quality and reusability.

  • https://archive.ph/IQfrH

• FAIR Principles: Interpretations and Implementation Considerations

  • Category: Data Management, FAIR Implementation

  • Context: Offers practical guidance on implementing the FAIR principles in real-world research.

  • https://archive.ph/32Xcy

• The Anatomy of a Nanopublication

  • Category: Data Sharing, Nanopublications

  • Context: Explains the structure and components of nanopublications, enhancing transparency and reproducibility.

  • https://archive.ph/jdT1S

• The Comparative Anatomy of Nanopublications and FAIR Digital Objects

  • Category: Data Sharing, FAIR Digital Objects

  • Context: Compares nanopublications with FAIR Digital Objects, improving understanding of data sharing.

  • https://archive.ph/Mqqli

• Percolation Theory

  • It mathematically studies connected clusters forming in random graphs or lattices, modeling phenomena like fluid flow through porous media.

  • Percolation analyzes phase transitions, identifying critical thresholds where large-scale connectivity suddenly emerges across the system.

  • In knowledge graphs, it helps optimize by identifying crucial connections and assessing network robustness or information diffusion pathways.

  • https://en.wikipedia.org/wiki/Percolation_theory

BioTech and TechBio Perspectives

• The Techbio Idea Maze: To Be or Not (Shawn Dimaantha)

  • Category: Strategic Analysis, Techbio Landscape

  • Context: Explores the complexities and challenges of navigating the "idea maze" within the techbio field, emphasizing the need for innovative approaches.

  • https://shawndimantha.substack.com/p/the-techbio-idea-maze-to-be-or-not

• Why We Haven't Made Breakthrough Medical Discoveries (Shawn Dimaantha)

  • Category: Medical Research, Innovation Challenges

  • Context: Delves into the reasons behind the stagnation of breakthrough medical discoveries, examining limitations in current research methodologies.

  • https://shawndimantha.substack.com/p/why-we-havent-made-breakthrough-medical-b28

• Vincent Alessi Podcast Interview

  • Category: Personal Insights, Career Perspectives

  • Context: Provides insights into Vincent Alessi's career and perspectives, relevant to a hackathon focused on knowledge graphs.

  • https://podcasts.apple.com/us/podcast/vincent-alessis-advanced-materials-exit-and-journey/id1532346146?i=1000669661353&l=ar

• Bits in Bio Newsletter

  • Category: Current Events, Bio/AI Trends

  • Context: Vincent Alessi's newsletter offers current events and perspectives on the intersection of biology and AI.

  • https://bitsinbio.substack.com/

Additional BioHack Reading Materials

• Unifying Large Language Models and Knowledge Graphs: A Roadmap

• Harmonizing quality measures of FAIRness assessment towards machine-actionable quality information

• Discovering Datasets on the Web Scale: Challenges and Recommendations for Google Dataset Search

• Knowledge Graphs as a source of trust for LLM-powered enterprise question answering

• Large Language Models, Knowledge Graphs and Search Engines: A Crossroads for Answering Users' Questions

• LLM-based SPARQL Query Generation from Natural Language over Federated Knowledge Graphs

• SPARQL Generation with Entity Pre-trained GPT for KG Question Answering

• GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer

• ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget

• When Search Engine Services meet Large Language Models: Visions and Challenges

• SciAgents: Automating scientific discovery through multi-agent intelligent graph reasoning

• From Local to Global: A Graph RAG Approach to Query-Focused Summarization

• OG-RAG: Ontology-Grounded Retrieval-Augmented Generation For Large Language Models

• https://www.sciencedirect.com/science/article/pii/S1570826824000398?via%3Dihub

• On the performativity of SDG classifications in large bibliometric databases

• Envisioning Information Access Systems: What Makes for Good Tools and a Healthy Web?

• Increasing the LLM Accuracy for Question Answering: Ontologies to the Rescue!