ReviewOncogene2008
Using biointelligence to search the cancer genome: an epistemological perspective on knowledge recovery strategies to enable precision medical genomics.
Review in Oncogene, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Clinical Implementation of Integrated Genomic Profiling in Patients with Advanced Cancers.Scientific reports · 2016Article
- The BioIntelligence Framework: a new computational platform for biomedical knowledge computing.Journal of the American Medical Informatics Association : JAMIA · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Genomic profiling is beginning to extend beyond the many applications in discovery research toward direct medical applications that hold the promise of more precise and individualized health-care delivery. There are many barriers and challenges that still need to be overcome before 'Precision Medical Genomics' can deliver the promise of more informed patient care, not the least of which is the unmet need for a new conceptual framework for recovering, understanding and translating potentially useful information from a single genome. Although a wide spectrum of scientific strategies, bioinformatic approaches, IT tools and knowledge resources have been developed to support discovery research, the interpretive requirements for recovering clinically useful insights from an individual's genome are different in many ways from those of traditional research goals. In this study, we compare and contrast the fundamental conceptual differences that distinguish 'research' to discover generalized knowledge from 'search' to recover individualized knowledge. We also consider the merits of applying evidence-based medicine and traditional scientific methods when n=1, and consider an alternative perspective based on a translational engineering approach and intelligence for interpreting genomic information from an individual case. Although the general idea of biological intelligence-based knowledge recovery that we introduce here can be broadly applied for personal genomics across many indications in medicine, we make a case that the need for adopting such a paradigm is greatest for supporting the management of complex diseases, and particularly suited for supporting therapeutic decisions in medical oncology. Early concepts for designing and implementing this kind of 'BioIntelligence' solution will be discussed. We also review the anticipated challenges of implementing genomic analysis and biological intelligence-based solutions in the practice of medical oncology by discussing some of the related pragmatic considerations for deploying the first generation of a 'Precision Medical Genomics' solution that can evolve and improve over time.
Indexed as
Identifiers
19956181What 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.