ReviewNPJ systems biology and applications2021
Nobel Turing Challenge: creating the engine for scientific discovery.
Review in NPJ systems biology and applications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed.
- Creating an engine of scientific discovery, an Indo-Japan perspective: learnings from IJNTC 2025 workshop.NPJ systems biology and applications · 2026Review
- The future of fundamental science led by generative closed-loop artificial intelligence.Frontiers in artificial intelligence · 2026Review
- Article
- AI-Assisted Tools for Scientific Review Writing: Opportunities and Cautions.ACS applied materials & interfaces · 2025Review
- When ChatGPT Writes Your Research Proposal: Scientific Creativity in the Age of Generative AI.Journal of Intelligence · 2025Article
- A comprehensive large scale biomedical knowledge graph for AI powered data driven biomedical research.bioRxiv : the preprint server for biology · 2025Article
- Automating the practice of science: Opportunities, challenges, and implications.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Redefining Roles: A Paradigm Shift in Tryptophan-Kynurenine Metabolism for Innovative Clinical Applications.International journal of molecular sciences · 2024Review
- Machine learning in drug delivery.Journal of controlled release : official journal of the Controlled Release Society · 2024Review
- Self-Driving Laboratories for Chemistry and Materials Science.Chemical reviews · 2024Review
- Beyond protein lists: AI-assisted interpretation of proteomic investigations in the context of evolving scientific knowledge.Nature methods · 2024Article
- Evolving scientific discovery by unifying data and background knowledge with AI Hilbert.Nature communications · 2024Article
- Towards Machine-FAIR: Representing software and datasets to facilitate reuse and scientific discovery by machines.Journal of biomedical informatics · 2024Article
- The automated lab of tomorrow.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Article
- Data-Driven Hypothesis Generation in Clinical Research: What We Learned from a Human Subject Study?Medical research archives · 2024Article
- A dynamic knowledge graph approach to distributed self-driving laboratories.Nature communications · 2024Article
- Data-driven hypothesis generation among inexperienced clinical researchers: A comparison of secondary data analyses with visualization (VIADS) and other tools.Journal of clinical and translational science · 2024Article
- Using think-aloud protocol to identify cognitive events while generating data-driven scientific hypotheses by inexperienced clinical researchers.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Asking the right questions for mutagenicity prediction from BioMedical text.NPJ systems biology and applications · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Scientific discovery has long been one of the central driving forces in our civilization. It uncovered the principles of the world we live in, and enabled us to invent new technologies reshaping our society, cure diseases, explore unknown new frontiers, and hopefully lead us to build a sustainable society. Accelerating the speed of scientific discovery is therefore one of the most important endeavors. This requires an in-depth understanding of not only the subject areas but also the nature of scientific discoveries themselves. In other words, the "science of science" needs to be established, and has to be implemented using artificial intelligence (AI) systems to be practically executable. At the same time, what may be implemented by "AI Scientists" may not resemble the scientific process conducted by human scientist. It may be an alternative form of science that will break the limitation of current scientific practice largely hampered by human cognitive limitation and sociological constraints. It could give rise to a human-AI hybrid form of science that shall bring systems biology and other sciences into the next stage. The Nobel Turing Challenge aims to develop a highly autonomous AI system that can perform top-level science, indistinguishable from the quality of that performed by the best human scientists, where some of the discoveries may be worthy of Nobel Prize level recognition and beyond.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.