Background: Vasopressin type 2 receptor (V2R) plays an important role in the water reabsorption in the kidney collecting ducts. V2R is a G protein coupled receptor (GPCR) and the triplet of amino acids aspartate-arginine-histidine (DRH) in this receptor might significantly influence its activity similar to other GPCR. However, the role of this motif has not been fully confirmed. Therefore, the ...

UNLABELLED 'Melina' assists users to compare the results of four public softwares for DNA motif extraction in order to both confirm the reliability of each finding and avoid missing important motifs. It is also useful to optimize the sensitivity of software with a series of different parameter settings. AVAILABILITY Melina is available at http://www.hgc.ims.u-tokyo.ac.jp/Melina/.

It is known that genes with similar expression profile are likely to be regulated by a common transcription factor and finding the common cis-element to which the protein binds from the upstream regions of these genes is very important. Although several famous programs for motif extraction exist nowadays, end-users often hesitate about the reliability of the output results. One reason is that t...

Infant-directed speech (IDS) is thought to play a key role in determining infant language acquisition. It is thus important to describe how computational models of infant language acquisition behave when given an input of IDS, as compared to adult-directed speech (ADS). In this paper, we explore how an acoustic motif discovery algorithm fares when presented with speech from both registers. Resu...

Motif discovery for the identification of functional regulatory elements underlying gene expression is a challenging problem. Sequence inspection often leads to discovery of novel motifs (including transcription factor sites) with previously uncharacterized function in gene expression. Coupled with the complexity underlying tissue-specific gene expression, there are several motifs that are puta...

Deep learning on graphs and in particular, graph convolutional neural networks, have recently attracted significant attention in the machine learning community. Many of such techniques explore the analogy between the graph Laplacian eigenvectors and the classical Fourier basis, allowing to formulate the convolution as a multiplication in the spectral domain. One of the key drawback of spectral ...

Computational protein design relies on a number of approximations to efficiently search the huge sequence space available to proteins. The fixed backbone and rotamer approximations in particular are important for formulating protein design as a discrete combinatorial optimization problem. However, the resulting coarse-grained sampling of possible side-chain terminal positions is problematic for...

Unravelling the underlying mechanisms of protein interactions requires knowledge about the interactions' binding sites. In this paper, we use a novel concept, binding motif pairs, to describe binding sites. A binding motif pair consists of two motifs each derived from one side of the binding protein sequences. The discovery is a directed approach that uses a combination of two data sources: 3-D...

We assess the potential of network motif profiles to characterize networks in much the same way that a bag-of-words strategy allows text documents to be compared in a vector space framework. This work was originally published in [1].This is potentially valuable as a generic strategy for comparing networks, particularly ego networks, in structural terms. The basic strategy is shown in Figure 1. ...