LOGICOIL: multi-state prediction of coiled-coil oligomeric
state.
Thomas L. Vincent <tlfvincent@gmail.com>, Peter J. Green and Derek N. Woolfson <D.N.Woolfson@bristol.ac.uk>
This package contains the functions necessary to run the LOGICOIL algorithm. LOGICOIL can be used to differentiate between antiparallel dimers, parallel dimers, trimers and higher-order coiled-coil sequence. By covering >90 percent of the known coiled-coil structures, LOGICOIL is a net improvement compared with other existing methods, which achieve a predictive coverage of around 31 percent of this population. As such, LOGICOIL is particularly useful for researchers looking to characterize novel coiled-coil sequences or studying coiled-coil containing protein assemblies. It may also be used to assist in the structural characterization of synthetic coiled-coil sequences.

Functions, Data and Code for Binary and Binomial Data
Joseph M Hilbe <hilbe@asu.edu>, Rafael S. de Souza <rafael.2706@gmail.com>
Functions, data and code for Hilbe, J.M. 2015. Practical Guide to Logistic Regression, by Chapman and Hall/CRC.
caret, pROC, ggplot2, ggthemes, reshape, e1071, MASS

caret, pROC, ggplot2, reshape, e1071, MASS

c(person("Jean-Karim", "Heriche", email = "heriche@embl.de", role = c("cre","aut")))
Read, register and compare point sets from single molecule localization microscopy.
stats, data.table, parallel, doParallel, foreach, TDA, proxy,
reshape2, pracma, transport, RANN, ff, aws, dbscan, EBImage

c(person("Jean-Karim", "Heriche", email = "heriche@embl.de", role = c("cre","aut"), comment = c(ORCID = "0000-0001-6867-9425")))
Rcpp, FNN, stats, data.table, parallel, doParallel, foreach,
proxy, reshape2, pracma, transport, RANN, ff, aws, dbscan,
EBImage
Jean-Karim Heriche [cre, aut] (<https://orcid.org/0000-0001-6867-9425>)

Change-point detection algorithm with
label constraints and a penalty for each change outside of labels.
Read TD Hocking, A Srivastava (2020) <arXiv:2006.13967> for details.

Missing morphometric data simulation and estimation
LOST includes functions for simulating missing
morphometric data randomly, with taxonomic bias and with
anatomical bias. This package also includes functions for
estimating missing morphometric data based on regression.