Computational Biology

Gene Set Enrichment Methods:
ASSESS: Analysis of Sample Set Enrichment ScoreS
cERMIT: Evidence-Ranked Motif IdenTification
GSAA: Gene Set Association Analysis
GSEA: Gene Set Enrichment Analysis

Statistical and quantitative genetics:
BFR-G: Inference of Additive Genetic Covariance (G) Matrix for High-dimensional Trait Data
Metagenomics:
FastPCA: Inference of Population Structure for Massive Genotype Data
HOMINID: Associatiing OTUs to Host Genotypes
MAPIT: MApping ePIstaTic QTL
WHODAD: Paternity Inference from Low-Coverage Sequencing Data
PhILR: Compositional Analysis of Metagenomic Data

Radiogenomics:
SECT: Predicting Disease Outcome from Imaging and Genomic Data

Geometric morphometrics:
Auto3DGM: Automated Alignment of 3D Shapes


Learning and Inference
arLMM: approximate ridge Linear Mixed Models
ARSVD: Adaptive Randomized SVD
BAKR: Bayesian Kernel Regression with Variable Selection
BMI: Localized Supervised Dimension Reduction using Bayesian Mixture Models
KSIR: Nonlinear Supervised Dimension Reduction using Kernels
LSIR: Localized Nonlinear Supervised Dimension Reduction
MELD: Fast Moment Estimation for Generalized Latent Dirichlet Models
MoS: Learning Mixture of Subspaces of Different Dimensions
PFR: Predictor-Dependent Shrinkage for Linear Regression
SIGP: Subspace Induced Gaussian Processes
SynCut: Learning Group Actions from Data


Computational Music
Classical Music Composition Using State Space Models