PhytoAFP: In Silico Approaches for Designing Plant-Derived Antifungal Peptides

Emerging infectious diseases (EID) are serious problems caused by fungi in humans and plant species. They are a severe threat to food security worldwide. In our current work, we have developed a support vector machine (SVM)-based model that attempts to design and predict therapeutic plant-derived antifungal peptides (PhytoAFP). The residue composition analysis shows the preference of C, G, K, R, and S amino acids. Position preference analysis shows that residues G, K, R, and A dominate the N-terminal. Similarly, residues N, S, C, and G prefer the C-terminal. Motif analysis reveals the presence of motifs like NYVF, NYVFP, YVFP, NYVFPA, and VFPA. We have developed two models using various input functions such as mono-, di-, and tripeptide composition, as well as binary, hybrid, and physiochemical properties, based on methods that are applied to the main data set. The TPC-based monopeptide composition model achieved more accuracy, 94.4%, with a Matthews correlation coefficient (MCC) of 0.89. Correspondingly, the second-best model based on dipeptides achieved an accuracy of 94.28% under the MCC 0.89 of the training dataset.

Position preference of essential genes in prokaryotic operons

Essential genes, which form the basis of life activities, are crucial for the survival of organisms. Essential genes tend to be located in operons, but how they are distributed in operons is still unclear for most prokaryotes. In order to clarify the general rule of position preference of essential genes in operons, an index of the average position of genes in an operon was proposed, and the distributions of essential and non-essential genes in operons in 51 bacterial genomes and two archaeal genomes were analyzed based on this new index. Consequently, essential genes were found to preferentially occupy the front positions of the operons, which tend to be expressed at higher levels.

Validation of population receptive field estimates in human visual cortex

Population receptive field (pRF) analysis has become a popular method for non-invasively inferring the spatial tuning properties of the human visual system and for reconstructing brain activity in visual space. Yet few studies have sought to validate pRF parameter estimates or systematically compared them between different methods. Here we used pRF models to reconstruct the visual cortex response to pseudo-randomly placed ‘constellation’ stimuli. We present different methods for visualizing brain activity in visual space. Compared to typically used back-projection of pRF profiles, we show that a searchlight approach using only pRF location greatly improves the spatial precision of reconstructions. We further quantify the precision with which different pRF estimates distinguish between stimulated and unstimulated parts of the visual field. Both combined wedge-and-ring and more conventional sweeping-bar stimuli afford excellent localization of the presented test stimuli. Even a probabilistic pRF model based on cortical anatomy without any retinotopic mapping data performs well albeit with lower precision than empirical data. Our findings demonstrate that pRF analysis is an accurate and robust method for mapping the position preference of voxels in human visual cortex.

Correction notice to: Position preference and position change of hiders in the game of hide-and-seek

Sanderson YB (2018). Position preference and position change of hiders in the game of hide-and-seek. Quarterly Journal of Experimental Psychology. 71(5): 1172–1187. doi: 10.1080/17470218.2017.1322110. The following errors were present in the Online First version of this article: Permissions acknowledgements were missing from legends to Figures 1, 2 and 3. Figure 2 has been replaced with an updated version. The Online First version of the article has been updated with these changes and subsequent versions of the article will be corrected.

Position preference and position change of hiders in the game of hide-and-seek

We study common tendencies adult hiders have in choosing and changing positions in the game of hide-and-seek. In our case, the game takes the form of commercial and homemade advent calendars in which the creator has hidden Numbers 1, 2, . . ., 24 in a seemingly random way. By comparing the numberings in the 332 human-generated calendars with random numberings, we identify common tendencies that hiders share. We observe that hiders hide things far apart and spread out from each other, the behavior which is consistent with, but concurrently extends previous research on hiding and its connection with subjective randomness.