Social Touch Gesture Recognition using Random Forest and Boosting on Distinct Feature Sets

Touch is a primary nonverbal communication channel used to communicate emotions or other social messages. Despite its importance, this channel is still very little explored in the affective computing field, as much more focus has been placed on visual and aural channels. In this paper, we investigate the possibility to automatically discriminate between different social touch types. We propose five distinct feature sets for describing touch behaviours captured by a grid of pressure sensors. These features are then combined together by using the Random Forest and Boosting methods for categorizing the touch gesture type. The proposed methods were evaluated on both the HAART (7 gesture types over different surfaces) and the CoST (14 gesture types over the same surface) datasets made available by the Social Touch Gesture Challenge 2015. Well above chance level performances were achieved with a 67% accuracy for the HAART and 59% for the CoST testing datasets respectively

Phylogeny

the folder contains files which contains sequences of CCD genes and their accession numbers. it also contains alignment file and the resulting phylogenetic tre

A schematic diagram of the proposed picroside pathway in <i>Picrorhiza kurrooa.</i>

<p>Picrosides are derived from geranyl diphosphate that can be synthesized both from cytoplasmic MVA and plastidic MEP pathways. CPR: cytochrome P450 reductase; G10H: geraniol 10-hydroxylase; 10 HGO: 10-hydroxygeraniol oxidoreductase; IRS: Iridoid synthase; PAL: phenylalanine ammonia-lyase; C4H: cinnamoyl 4-hydroxylase; Route I: The route leading to the biosynthesis of secologanin, Route II: The route leading to the biosynthesis to picrosides <i>via</i> catalpol. Adapted from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073804#pone.0073804-Damtoft1" target="_blank">[62]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073804#pone.0073804-Mahmoud1" target="_blank">[63]</a>.</p

2-D representation of interactions of UGT86C4 and UGT94F2.

<p>2-D representation of the interaction figure (in pink) of kaempferol with UGT86C4 (A), and 2-D interaction figure of 7-deoxyloganetin with UGT94F2 (B).</p

Molecular docking of UGT94F2.

<p>Diagram showing (A) kaempferol (B) naringenin (C) apigenin (D) 7-deoxyloganetin (E) 7-deoxyloganetic acid and (F) iridotrial docked into the proposed binding pockets of UGT94F2.</p

Three dimensional models and conserved residue prediction for UGT86C4 and UGT94F2.

<p>A and B: Ribbon display of the 3-D structures of UGT86C4 and UGT94F2 as predicted by PHYRE2 web server, using crystal structure <i>Arabidopsis thaliana</i> UGT72B1 (Protein Data Bank (PDB) Id. 2VCH-A) as template for modeling of both the proteins. N and C-terminal domains are shown. Donor and acceptor sites are also shown. C and D: Predicted ligand binding sites as predicted by 3DLigandSite web server. E and F: Evolutionary conserved residue analysis of UGT86C4 and UGT94F2 were performed using Consurf, an empirical Bayesian inference based web server. Residue conservation from variable to conserved is shown in blue (1) to violet (9). The residues involved in binding of the donor moieties are shown in the centre of the structures.</p

Nucleotide sequences of <i>Picrorhiza</i> UGT gene promoters.

<p>Nucleotide sequences of the UGT86C4 (A) and UGT94F2 (B) gene promoters. Numbering starts from the predicted transcription start site (dark green shaded). The putative core promoter consensus sequences and the motifs with significant similarity to the previously identified <i>cis</i>-acting elements are shaded and the names are given.</p

Molecular Characterization of UGT94F2 and UGT86C4, Two Glycosyltransferases from <i>Picrorhiza kurrooa</i>: Comparative Structural Insight and Evaluation of Substrate Recognition

<div><p>Uridine diphosphate glycosyltransferases (UGTs) are pivotal in the process of glycosylation for decorating natural products with sugars. It is one of the versatile mechanisms in determining chemical complexity and diversity for the production of suite of pharmacologically active plant natural products. <i>Picrorhiza kurrooa</i> is a highly reputed medicinal herb known for its hepato-protective properties which are attributed to a novel group of iridoid glycosides known as picrosides. Although the plant is well studied in terms of its pharmacological properties, very little is known about the biosynthesis of these important secondary metabolites. In this study, we identified two family-1 glucosyltransferases from <i>P. kurrooa</i>. The full length cDNAs of UGT94F4 and UGT86C4 contained open reading frames of 1455 and 1422 nucleotides, encoding polypeptides of 484 and 473 amino acids respectively. UGT94F2 and UGT86C4 showed differential expression pattern in leaves, rhizomes and inflorescence. To elucidate whether the differential expression pattern of the two <i>Picrorhiza</i> UGTs correlate with transcriptional regulation <i>via</i> their promoters and to identify elements that could be recognized by known iridoid-specific transcription factors, upstream regions of each gene were isolated and scanned for putative <i>cis</i>-regulatory elements. Interestingly, the presence of <i>cis</i>-regulatory elements within the promoter regions of each gene correlated positively with their expression profiles in response to different phytohormones. HPLC analysis of picrosides extracted from different tissues and elicitor-treated samples showed a significant increase in picroside levels, corroborating well with the expression profile of UGT94F2 possibly indicating its implication in picroside biosynthesis. Using homology modeling and molecular docking studies, we provide an insight into the donor and acceptor specificities of both UGTs identified in this study. UGT94F2 was predicted to be an iridoid-specific glucosyltransferase having maximum binding affinity towards 7-deoxyloganetin while as UGT86C4 was predicted to be a kaempferol-specific glucosyltransferase. These are the first UGTs being reported from <i>P. kurrooa.</i></p></div

Molecular docking of UGT86C4.

<p>Diagram showing (A) kaempferol (B) naringenin (C) apigenin (D) 7-deoxyloganetin (E) 7-deoxyloganetic acid and (F) iridotrial docked into the proposed binding pockets of UGT86C4.</p

Binding affinity of ligand data set on modeled structures of UGT86C4 and UGT94F2.

<p>Binding affinity of ligand data set on modeled structures of UGT86C4 and UGT94F2.</p