CaPS	Webserver for prediction of EF-hand or EF-hand like Ca^2+-binding motifs	https://shenghuixue.github.io/CAPS/index.html
EF-hand CaBPs data library	Database of sequence and structural information on EF-hand CaBPs	http://structbio.vanderbilt.edu/cabp_database/cabp.html
EF-Handome	A collection of gene, mRNA and protein information of EF-hand proteins in human, rat and mouse	Available from the authors
MFSCa	A meta-functional signature algorithm for Ca^2+-binding residue prediction	Available from the authors
MetalloPred	Webserver for prediction of metal-binding sites using cascade of neural networks from sequence derived features	http://www.juit.ac.in/attachments/Metallopred/prediction.html
CalPred	Web tools for EF-hand CaBP prediction and calcium binding region identification	http://www.bioinformatics.org/calpred/index.html
Predicting Ca^2+-binding sites based on protein structures (PDB entries or modeled structures)
MUG^π	Tools for predicting Ca^2+-binding sites based on graph theory and geometric analyses	https://calciomics.org/
Fold-X	A computations algorithm based on empirical force field to predict the position of metal ions in protein	http://foldx.crg.es/
SVMProt	Webserver for assigning protein functions (including Ca^2+-binding) with support vector machine learning	http://bidd2.nus.edu.sg/cgi-bin/svmprot/svmprot.cgi
WebFEATURE	Webserver for automated function prediction (including Ca^2+-binding sites) in protein structures with machine learning
SitePredict	Webserver for predicting metal ion binding sites with the Random Forest machine learning method
FunFOLD	An integrated web resource for ligand binding site prediction	http://www.reading.ac.uk/bioinf/FunFOLD/FunFOLD_form.html
FINDSITE-metal	A threading-based method to detect metal-binding site in modeled structures by integrating evolutionary information and machine learning
MetaPocket	A consensus method to predict ligand binding sites by integrating LIGSITE, PASS, Q-SiteFinder and SURFNET, Fpocket, GHECOM, ConCavity and POCASA
MetSite	An automatic approach for detecting metal-binding residues in low-resolution 3D models by with neural network classifiers
Predicting Ca^2+-modulated functions
Calmodulin Target Database	Webserver for predicting calmodulin binding sites from protein sequences	http://calcium.uhnres.utoronto.ca/ctdb/ctdb/home.html
MeTaDor	Webserver for predicting membrane targeting domains (e.g., Ca^2+-dependent C2 domain)
ORBIT	De novo design of protein sequence based on a desired backbone fold	Available from the authors
DEZYMER	Design of metal binding sties by selecting suitable ligands	Available from the authors