Highly accurate model for prediction of lung nodule malignancy with CT scans.

The software and supplemental material related to this publication is available at http://bioinformatics.astate.edu/NoduleX.

Causey, J. L., Zhang, J. et al. Highly accurate model for prediction of lung nodule malignancy with CT scans. Scientific Reports 8, 9286 (2018).

DNAp: A Pipeline for DNA-seq Data Analysis

The DNAp software and documentation is available to the public at http://bioinformatics.astate.edu/dna-pipeline/.

Causey, J. L. et al. DNAp: A Pipeline for DNA-seq Data Analysis. Scientific Reports 8, 6793 (2018).

SparRec: An effective matrix completion framework of missing data imputation for GWAS.

The framework of SparRec (Sparse Recovery) is implemented in MATLAB and the source code is available from: https://sourceforge.net/projects/sparrec/files/?source=navbar Or, http://bioinformatics.astate.edu/code2/ and also available on GitHub at: https://github.com/astate-bioinformatics/SparRec.

Jiang, B., Ma, S., Causey, J. et al. SparRec: An effective matrix completion framework of missing data imputation for GWAS. Scientific Reports 6, 35534 (2016).

SPARCoC: A New Framework for Molecular Pattern Discovery and Cancer Gene Identification.

The framework SPARCoC (Sparse-CoClust for Pattern Discovery and Cancer Molecular Subtyping) is implemented in MATLAB and the source code is available from: http://bioinformatics.astate.edu/code.

Ma, S., Johnson, D., Ashby, C. et al. SPARCoC: A New Framework for Molecular Pattern Discovery and Cancer Gene Identification. PLoS ONE 10, e0117135 (2015).