We are more than happy to share the following packages with other academic researchers. Some of the packages are password protected. To request thoes packages, please fill in and sign this code request form, and send it to yyl@channing.harvard.edu. We will review your request. If approved, we will send you the password to unzip those reqested packages. 

Note that the permission to use any of the following packages is granted by the authors, only on the following conditions:

1. These packages remain at your research group and should not be published, distributed, or otherwise transferred or made available to people other than your group members.
2. These packages should be used by you and/or your research group solely for non-commercial purposes.
3. You may provide us with feedback on the use of these packages in your research, and that we are permitted to use any information you provide in making changes to these packages with acknowledgement.
4. Any risk associated with using these packages at your institution or research group is with you and your institution.
5. These packages should be cited appropriately in any of your publication(s) reporting on data obtained by using them.

ControllabilityAnalysis: This is the C++ code accompanying the paper by Liu Y-Y, Slotine J-J, Barabási A-L. Controllability of complex networks. Nature (featured as a cover story) 2011;473:167–173. It will parse any two-column edgelist file and perform the controllability analysis, reporting the number of driver nodes, node classifications, link classifications, etc.

CalControlCentrality: This is the C++ code accompanying the paper by Liu Y-YL, Slotine J-J, Barabási A-L. Control Centrality and Hierarchical Structure in Complex Networks. PLOS ONE 2012;7:e44459.. It will parse any two-column edgelist file and calculate the control centrality of each node in the network.

MotifAnalysis: This is the Mathematica script accompanying the paper by Angulo MT, Liu Y-Y, Slotine J-J. Network motifs emerge from interconnections that favor stability. Nature Physics 2015;11:848-852. It will perform network motif analysis from real networks and their condensations. 

Qualitative Flux Control (QFC) Analysis: This is the Matlab package accompanying the paper by Basler G, Nikoloski Z, Larhlimi A, Barabási A-L, Liu Y-Y. Control of Fluxes in Metabolic Networks. Genome Research (featured as a cover story) 2016;26:956-968. It will calculate the driver reactions of metabolic networks. 

Dissimilarity-Overlap Curve (DOC) Analysis: This is the Matlab package accompanying the paper by Bashan A, Gibson TE, Friedman J, Carey VJ, Weiss ST, Hohmann EL, Liu Y-Y. Universality of Human Microbial Dynamics. Nature 2016;534:259-262. It will quantify the universality of human microbial dynamics by performing the DOC analysis over OTU table. 

Entropy-based consensus clustering (ECC): This is the Matlab package accompanying the paper by Liu H, Zhao R, Fang H, Cheng F, Fu Y, Liu Y-Y.  Entropy-based Consensus Clustering for Patient Stratification. Bioinformatics 2017;btx167:1-8. It will perform entropy-based consensus clustering, using multiple data types. 

Articulation Point (AP) Analysis: This is the C code accompanying the paper by Tian L, Bashan A, Shi D-N, Liu Y-Y. Articulation Points in Complex Networks. Nature Communications 2017;8:14223. It will perform the Greedy Articulation Points Removal (GAPR) decomposition for real networks. 

Ecological Network Reconstruction (NR): This is the Matlab package accompanying the paper by Xiao Y, Angulo MT, Friedman J, Waldor MK, Weiss ST, Liu Y-Y. Mapping the ecological networks of microbial communities. Nature Communications 2017;8:2042. It will reconstruct ecological network of microbial communities from steady-state data.