Journal of Theoretical Biology

To establish a quality benchmark dataset for developing a predictor to identify the functional types of membrane proteins, the sequences were collected from UniProtKB/ Swiss-Prot release on 2018_04 at http://www.uniprot.org/according to the following steps (Lin et al. 2013). Proteins belonging to all eight types were collected. Those proteins annotated with ‘‘fragment’’ were removed; meanwhile, those proteins with the length of sequence less than 50 residues were also excluded, in case of the influence of the fragment. Sequences annotated with ambiguous or uncertain terms, such as ‘‘potential,’’ ‘‘probable,’’‘‘probably,’’ ‘‘maybe,’’ or ‘‘by similarity,’’ were removed for further consideration. The Dataset 4 is divided as training dataset and testing dataset with 1332 and 1033 respectively.

SI3-1: 15 suggested theoretical configurations for the calculation of MDs (defined with the name projects). The selected configuration for the projects used in this study are also indicated in Table SI2-1 and are available at SI3-1. SI3-2: The experiments employed a dataset containing 152 representatives, non-homologous proteins (see SI3-2 to review the protein files). (Fleming and Richards, 2000). SI3-3: The evaluation of this application in protein science requires the use of two datasets. The first data set, employed as a training set, was proposed by Ouyang (Ouyang and Liang, 2008) and contains 80 proteins (the case “2BLM” was removed since it only considered an alpha carbon representation). The second dataset, employed as a test set, was proposed by Ruiz-Blanco (Ruiz-Blanco et al., 2015) and contains 17 proteins. SI3-4: For the generation of the models, a dataset of 204 proteins was employed. (Chou, 1999) The original dataset was split into two groups: a training set with 149 proteins and a test set containing 55 proteins to ensure a proper comparison (Marrero Ponce et al., 2015a)

I. The program Poly_map_2age produces maps classifying possibility of polymorphism maintenance for 2-age population under cyclical selection for two cases: (i) maternal selection (Eq. 5), (ii) simple gene (Eq. 6) in text format. a. Output notation: 0 and 1 are monomorphism, 3 is polymorphism, 4 is bistability region. b. To start: poly_map_2age.exe INP x_s.csv x_m.csv c. C++ cod (“poly_map_2age.CPP”), Input, and Output files examples are given in the current directory; II. Color_maps.R (script in R) transforms text output (“x_s.csv” and “x_m.csv”) to color image III. Poly_int_uniform.R (script in R) allows constructing figures with a. coexistence conditions for four- and three-year cycles with value variations of the parameter m. Separetedly for maternal selection (Eq. 2) and .simple gene (Eq. 1) b. coexistence conditions for N-year cycles at any fixed value of m.

The included Mathematica notebooks allow for analysis of the model describing the population dynamical consequences of antagonism between partners sharing a mutualist. "FullModelAnalyses.nb" could be used to recover all of our results. "RegionPlots.nb" provide code necessary to recreate region plots used in the paper. The other files are the supplementary files that show brief methods for obtaining (1) population dynamics of different ecological scenarios beyond those explored in depth in the manuscript, (2) stability analyses of model equilibria, (3) direct and indirect effects as evidenced by press perturbation analyses. Both .nb and .cdf files are provided.

For the years 1989- 1993, data provides whether an observation is a US Sugar Corporation field was infected with CTV. A '1' indicates infection a 0 otherwise. Headers "hor" and "vert" specify the row and column where an observations is located in the field. The headers 89-93 correspond to years 1989- 1993 respectively.

simulation results used in Fig 3 and the original script in python.

Names-position-nodes.csv is a tab delimited file that contains 83 rows. Each row has 7 entries: the node number, its hemisphere (left or right), its anatomical name, its coordinates (x,y,z), and its associated region.

Zombie ants are ants manipulated by a fungal parasite (Ophiocordyceps sp.) to leave the nest and die biting the underside of a leaf. From there, the fungus grows from the ant and distributes spores to new ants. The model recreates how infected ants are walking from the nest to the biting locations. By altering the movement parameters of the ants, we investigate how walking style influences whether ants frequently end up on the biting locations. The model uses field data to inform the model setup, using 4 different nests with the real locations of the ant nest, foraging trails, and cadaver biting locations.

All data for Goerlitz et al, J Theor Biol bat parameters, moth parameters, detection distances, buffer distances

Source code for running all simulations