Attention ========= Please expect issues with profnet-snapfun! It caused a Segmentation fault in an autopkgtest which was deactivated. This is documented in the bug report at https://bugs.debian.org/905206 In case this program might turn out to be totally useless we need to remove this binary package since there is no support from its authors any more. Please report any issue via reportbug profnet-snapfun profnet ======= profnet_* binaries are neural network implementations in Fortran. Due to the original design of the code, a specific binary is compiled for each particular network architecture, changing certain constants in the source code. Therefore, there is a binary for every network architecture used. Note: certain array structures are intentionally indexed out of bounds in some of the binaries! Q: Why so many binary packages? ------------------------------- There are a handful of prediction methods built around each of the binary profnet packages. Each depends on the matching profnet binary package. Each prediction method requires a different neural network architecture and therefore - due to the design of the code - a different binary. Binaries are compiled with constants set to the architecture of the network and are therefore not reusable for other architectures. To further develop the code beyond regular maintenance for compiler and architecture updates is not planned since a complete reimplementation of these networks with a neural network library is already underway. Publications of predictors that use these neural networks --------------------------------------------------------- Note: this list contains references only to the secondary structure and accessibility predictor (profnet-prof and profphd-net). References for the other methods are provided in the man pages of the respective methods' predictor commands, e.g. profbval(1). * Rost, B. and Sander, C. (1994a). Combining evolutionary information and neural networks to predict protein secondary structure. Proteins, 19(1), 55-72. * Rost, B. and Sander, C. (1994b). Conservation and prediction of solvent accessibility in protein families. Proteins, 20(3), 216-26. * Rost, B., Casadio, R., Fariselli, P., and Sander, C. (1995). Transmembrane helices predicted at 95 Protein Sci, 4(3), 521-33. -- Laszlo Kajan Tue, 14 Jun 2011 18:50:52 +0200