Statistical Software Packages:

1. CML: Coordinated multi-neighborhood learning on DAGs.
2. fact: Factor analysis via correlation thresholding.
3. scorelingam: Learning topological ordering of non-Gaussian linear DAGs.
4. phsl: Partitioned hybrid structure learning.
5. EAinference: Estimator augmentation and simulation-based inference.
6. sparsebn: Learning sparse Bayesian networks from high-dimensional data.
7. discretecdAlgorithm: Learning discrete Bayesian networks by coordinate descent.
8. ccdr: Concave penalized learning of Bayesian networks.
9. SPClustering: Solution path clustering via concave penalization.

Computational Biology Software:

1. TFKFunctions: Decting clustering and ordering binding patterns among transcription factors.
2. CMF: Contrast motif finder that finds motifs with differential enrichment between two datasets.
3. HtBackground: Building a heterogeneous background model for DNA multiple alignments.
4. MultiScan: Motif scan in multiple alignments with background built from HtBackground.
5. MultiModule: Motif-module discovery in multiple species by coupling hidden Markov models.
6. CisModule: De novo motif-module discovery algorithm based on a hierarchical mixture model.
7. CisModScan: Scanning for cis-regulatory modules given PWMs.
8. GMS-MP: Gibbs motif sampler for pare correlation model.