ArticleBMC bioinformatics2009
Willows: a memory efficient tree and forest construction package.
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Predictors of Abstinence From Heavy Drinking During Follow-Up in COMBINE.Journal of studies on alcohol and drugs · 2015Trial
- The effects of fermented pineapple residue on growth performance, meat quality, and rumen microbiota of fattening Simmental bull.Frontiers in microbiology · 2022Article
- Incorporating epistasis interaction of genetic susceptibility single nucleotide polymorphisms in a lung cancer risk prediction model.International journal of oncology · 2016Article
- The phenotypic manifestations of rare genic CNVs in autism spectrum disorder.Molecular psychiatry · 2015Article
- Predictors of abstinence from heavy drinking during treatment in COMBINE and external validation in PREDICT.Alcoholism, clinical and experimental research · 2014Article
- Data mining in the Life Sciences with Random Forest: a walk in the park or lost in the jungle?Briefings in bioinformatics · 2013Article
- De novo genome sequencing and comparative genomics of date palm (Phoenix dactylifera).Nature biotechnology · 2011Article
- Ranking causal variants and associated regions in genome-wide association studies by the support vector machine and random forest.Nucleic acids research · 2011Article
- Power of data mining methods to detect genetic associations and interactions.Human heredity · 2011Article
- On safari to Random Jungle: a fast implementation of Random Forests for high-dimensional data.Bioinformatics (Oxford, England) · 2010Article
- Bioinformatics challenges for genome-wide association studies.Bioinformatics (Oxford, England) · 2010Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundExisting tree and forest methods are powerful bioinformatics tools to explore high dimensional data including high throughput genomic data. However, they cannot deal with the data generated by recent genotyping platforms for single nucleotide polymorphisms due to the massive size of the data and its excessive memory demand.
resultsUsing the recursive partitioning technique, we developed a new software package, Willows, to maximize the utility of the computer memory and make it feasible to analyze massive genotype data. This package includes three tree-based methods -- classification tree, random forest, and deterministic forest, and can efficiently handle the massive amount of SNP data. In addition, this package can easily set different options (e.g., algorithms and specifications) and predict the class of test samples.
conclusionWe developed Willows in a user friendly interface with the goal of maximizing the use of memory, which is critical for analysis of genomic data. The Willows package is well documented and publicly available at (http://c2s2.yale.edu/software/Willows).
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.