In the spirit of reproducible research, my collaborators and I have generally aimed to create and freely distribute prototype software implementations of the methodologies developed in our research work. The older stuff is available through this webpage. Since roughly 2015, we have tried instead to distribute consistently through my research group’s Github pages.
Please note that while we have done our best to comment the code sufficiently and test it, this is being made available `as is’. There have been no attempts to maintain the software, for example in terms of compatability with successive releases of the Matlab or alternate operating systems. Nor is any promise of `support’ being made in releasing the code, although of course I will answer any questions as best I can. Therefore, as the saying goes, caveat emptor.
Software for Network-Based Research
- Network Auto-Probit Modeling for Binary Network Processes Jiang, X., Gold, D.L., and Kolaczyk, E.D. (2009). Network-based auto-probit modeling for protein function prediction. Biometrics, (revised; under review).Zip-file with software and data for network-based auto-probit method introduced in this paper.
- Network IntegrationJiang, X., Nariai, N., Steffen, M., Kasif, S., and Kolaczyk, E.D. (2007). Integration of Relational and Hierarchical Network Information for Protein Function Prediction. BMC Bioinformatics, 9:350.Zip-file with software and data for hierarchical binomial neighborhood (HBN) method introduced in this paper.
- Group Betweenness / Co-BetweennessKolaczyk, E.D., Chua, D.B., and Barthelemy, M. (2007). Group Betweenness and Co-Betweenness: Inter-related Notions of Coalition Centrality. Social Networks, 31:3, 190-203 . Zip-file with software for computing group betweenness bounds based on vertex co-betweenness.
- Latent Pathway Idenfication Analysis (LPIA)Pham, L., Christadore, L., Schaus, S., and Kolaczyk, E.D. (2011). Network-based prediction for sources of transcriptional dysregulation via latent pathway identification analysis. Proceedings of the National Academy of Sciences, doi: 10.1073/pnas.1100891108.Software for identifying latent pathways is available at the LPIA webpage.
- Detection of Gene-Gene InteractionsLu, C., Latourelle, J., O’Connor, G.T., Dupuis, J., and Kolaczyk, E.D. (2013). Network-guided sparse regression modeling for detection of gene-by-gene interactions. Bioinformatics, 29(10), 1241-1249. Zip-file with software for implementing the method described in the paper.
Software for Multiscale Reseach
- Translation Invariant Poisson Smoothing using Haar wavelets (TIPSH):Kolaczyk, E.D. and Dixon, D.D. (2000). Nonparametric estimation of intensity maps using Haar wavelets and Poisson noise characteristics. The Astrophysical Journal, 534:1, 490-505.Website with software to do TIPSH analysis. Also, please download from here an additional file missing from the original set of TIPSH software files.
- Multiscale Methods for Poisson Count Data:
- Estimation:Kolaczyk, E.D. (1999). Bayesian Multi-Scale Models for Poisson Processes. Journal of the American Statistical Association, 94, 920-933. Tar-file with software for estimation algorithm described in paper.
- Deconvolution:Nowak, R.D. and Kolaczyk, E.D. (2000). A Bayesian multiscale framework for Poisson inverse problems. IEEE Transactions on Information Theory, 46:5, 1811-1825. Tar-file with software for one-dimensional implementation of deconvolution algorithm described in paper.
- Segmentation:Kolaczyk, E.D. (2003). Bayesian multiscale methods for Poisson count data. In Statistical Challenges in Modern Astronomy III (eds. G.J. Babu & E.D. Feigelson), New York:Springer-Verlag. Tar-file with software for one-dimensional implementation of segmentation algorithm described in paper.
- Multiscale Generalized Linear Models (MS-GLMs) Kolaczyk, E.D. and Nowak, R.D. (2005). Multiscale generalized linear models for nonparametric function estimation. Biometrika, 92 (1), 119-133. Zipped-file with software for Poisson and binomial time series.
- Multiscale, Multigranular Image Segmentation (MSMG) Kolaczyk, E.D., Ju, J., and Gopal, S. (2005). Multiscale, multigranular statistical image segmentation. Journal of the American Statistical Association, 100 (472), 1358-1369. Zipped-file with software for multiscale, multigranular image segmentation.