Spinach (Spinacia oleracea L.) is an economically important leafy vegetable crop in many countries. This is the first case study of using SRAP markers to analyze genetic diversity of Iranian spinach accessions. Eight SRAP primer combinations generated 88 scorable bands ranging from 50 to 1000 bp, among which 73 were polymorphic, with an average of 82.9 polymorphic bands per primer combination a...

Abstract Addressing a quest by Gupta et al. (in: Proceedings of the 41st international colloquium on automata, languages, and programming (ICALP 2014), vol 8572 LNCS. Springer, pp 563–575, we provide first, comprehensive study finding short s – t path in multistage graph model, referred to as Multistage Path problem. Herein, given sequence graphs over same vertex set but changing edge sets, tas...

In real life biomedical classification applications, feature space may be of high dimension in which visualization of class distribution is impossible. Moreover, attributes of features may be numeric, ordinal, categorical or binary. Most of the time, features may be composed of mixed type of attributes. In this paper, the concept of similarity-dissimilarity is extended to various types of attri...

Tree edit distance is a conventional dissimilarity measure between labeled trees. However, tree edit distance including unit-cost edit distance contains the similarity of label and that of tree structure simultaneously. Therefore, even if the label similarity between two trees that share many nodes with the same label is high, the high label similarity is hard to be recognized from their tree e...

We propose a novel interest point detector stemming from the intuition that image patches which are highly dissimilar over a relatively large extent of their surroundings hold the property of being repeatable and distinctive. This concept of contextual self-dissimilarity reverses the key paradigm of recent successful techniques such as the Local Self-Similarity descriptor and the Non-Local Mean...

Identifying groups of genes that manifest similar expression patterns is crucial in the analysis of gene expression time series data. Choosing a similarity measure to determine the similarity or distance between profiles is an important task. This paper proposes a suitable dissimilarity measure for gene expression time series data sets. It also presents a graph-based clustering method for findi...

Partitioning a data set and extracting hidden structure from the data arises in different application areas of pattern recognition, speech and image processing. Pairwise data clustering is a combinatorial optimization method for data grouping which extracts hidden structure from proximity data. We describe a deterministic annealing approach to pairwise clustering which shares the robustness pro...