ArticleStatistics in biosciences2016
Strategies for Genomic and Proteomic Profiling of Cancers.
Article in Statistics in biosciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- LGBM-ACp: an ensemble model for anticancer peptide prediction and in silico screening with potential drug targets.Molecular diversity · 2024Article
- To Assist Oncologists: An Efficient Machine Learning-Based Approach for Anti-Cancer Peptides Classification.Sensors (Basel, Switzerland) · 2022Article
- CancerPDF: A repository of cancer-associated peptidome found in human biofluids.Scientific reports · 2017Article
- HCSD: the human cancer secretome database.Database : the journal of biological databases and curation · 2015Article
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
Abstract
Omics-based technology platforms have made new kinds of cancer profiling tests feasible. There are several valuable examples in clinical practice, and many more under development. A concerted, transparent process of discovery with lock-down of candidate assays and classifiers and clear specification of intended clinical use is essential. The Institute of Medicine has now proposed a three-stage scheme of confirming and validating analytical findings, validating performance on clinical specimens, and demonstrating explicit clinical utility for an approvable test (Micheel et al., Evolution of translational omics: lessons learned and path forward, 2012).
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.