Data Mining Practical Machine Learning Tools and Techniques

We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

The Strategy of the Genes

Deep learning in spiking neural networks

Nothing is solid about proteins. Governing rules and established laws are constantly broken. As an example, the last decade and a half have witnessed the fall of one of the major paradigms in structural biology. Contrarily to the more than a century-old belief that the unique function of a protein is determined by its unique structure, which, in its turn, is defined by the unique amino acid sequence, many biologically active proteins lack stable tertiary and/or secondary structure either entirely or at their significant parts. Such intrinsically disordered proteins (IDPs) and hybrid proteins containing ordered domains and functional IDP regions (IDPRs) are highly abundant in nature, and many of them are associated with various human diseases. Such disordered proteins and regions are very different from ordered and well-structured proteins and domains at a variety of levels and possess well-recognizable biases in their amino acid compositions and amino acid sequences. A characteristic feature of these proteins is their exceptional structural heterogeneity, where different parts of a given polypeptide chain can be ordered (or disordered) to different degrees. As a result, a typical IDP/IDPR contains a multitude of potentially foldable, partially foldable, differently foldable or not foldable structural segments. This distribution of conformers is constantly changing in time, where a given segment of a protein molecule has different structures at different time points. The distribution is also constantly changing in response to changes in the environment. This mosaic structural organization is crucial for their functions and many IDPs are engaged in biological functions that rely on high conformational flexibility and that are not accessible to proteins with unique and fixed structures. As a result, the functional repertoire of IDPs complements that of ordered proteins, with IDPs/IDPRs being often involved in regulation, signaling and control. This Sprenger Briefs volume is dedicated to IDPs and IDPRs and an attempt is made to compress a massive amount of knowledge and into a digest that aims to be of use to those wishing a fast entry into this promising field of structural biology.

Intrinsically Disordered Proteins

In this paper A-sequences, which are integer sequences characterizing binary trees are introduced. These sequences generate directly and lexicographically all the binary trees in the reverse order of A-order. The generation algorithm with ranking and unranking are provided. Furthermore, the similarities and the differences of A-sequences with the similar previous works are discussed.

On the generation of binary trees in A-order

The function of an RNA sequence is related to its tertiary structure. Since dealing with RNA tertiary structure is very complicated, the RNA secondary structure is used instead. RNA secondary structure denotes various considerable aspects of RNA tertiary structure, and the biological function of an RNA sequence is assumed to be related to its secondary structure. Another useful illustration of an RNA secondary structure is the RNA shape, where it is holding the vicinity and nesting of structural components and shrinking their lengths to one. It would be significant to analyze the relations between the RNA sequences and their structures. One of the useful methods to perform these kinds of analysis is the neutral network. A neutral network can be considered as a graph whose vertex set is a collection of RNA sequences, all coding the same secondary structure, in which two RNA sequences are connected if one of them can be obtained from the other by a single base mutation. In this paper, a novel concept, entitled variation network, over the set of all RNA shapes is proposed to analyze the relation between the RNA sequences and their shapes, as well as to discover different topological properties of the RNA shapes. Based on the variation network, several topological properties, such as clustering coefficient, topological coefficient, average shortest path distribution, and centrality are calculated for natural RNA sequences. Also, the correlations between power-law function and some distributions over the variation network are obtained. These correlations indicate that the variation network is a kind of complex biological network, having scale-free structure and small world property. MATCH

Topological Properties of RNA Variation Networks over the Space of RNA Shapes

An efficient recursive a algorithm for the generating all shapes of binary trees with n-nodes is presented. A binary tree with n-nodes is represented by 2(n−1) zeros and ones in a certain predetermined order. This scheme encodes the non-null links of a binary tree by 1's and the null links by 0's in a pre-order traversal. The algorithm generates C n numbers of such codes. The algorithm is based on the idea of shifting ‘1' bits one space to the right. It is shown that the generation time per tree is constant O(1). The ranking and unranking algorithms are discussed. Also, an alternate way to obtain the Catalan numbers is given.

On the generation of binary trees from (0–1) codes

One of the fundamental problems in computational biology is the construction of physical maps of chromosomes from the hybridisation experiments between unique probes and clones of chromosome fragments. Before introducing the shotgun sequencing method, Partial Digest Problem PDP was an intractable problem used to construct the physical maps of DNA sequence in molecular biology. In this paper, we develop a novel Genetic Algorithm GA for solving the PDP. This algorithm is implemented and compared with well-known existing algorithms on different types of random and real instances data, and the obtained results show the efficiency of our algorithm. Also, our GA is adapted to handle the erroneous data and their efficiency is presented for the large instances of this problem.

Genetic algorithm solution for partial digest problem

Two parallel algorithms are presented for solving the minimum cost spanning tree problem in any undirected graph. These algorithms are parallel formulations of DHEA algorithm using Depth-First Search of the graph. The cost-optimality of both algorithms are investigated.

Abbas Nowzari-Dalini

Papers

On the generation of binary trees in A-order

Topological Properties of RNA Variation Networks over the Space of RNA Shapes

On the generation of binary trees from (0–1) codes

Genetic algorithm solution for partial digest problem

Parallel Algorithms for Minimum Spanning Tree Problem