Исследование репертуара TCR монозиготных и дизиготных близнецов
The paper formulates the problem of constructing a broadly applicable and flexible Conceptual Metagrammar (CM). It is to be a collection of the rules enabling us to construct step by step a semantic representation (or text meaning representation) of practically arbitrary sentence or discourse pertaining to mass spheres of human’s professional activity. The opinion is grounded that the first version of broadly applicable and flexible CM is already available in the scientific literature. It is conjectured that the definition of the class of SK-languages (standard knowledge languages) provided by the theory of K-representations (knowledge representations) can be interpreted as the first version of broadly applicable and flexible CM. The current version of the latter theory is stated in the author’s monograph published by Springer in 2010. The final part of the paper describes the connections with the related approaches, in particular, with the studies on developing a Multilingual Semantic Web.
The IEEE BIBM 2018 promises to provide great scientific quality and to have a broad impact, with world renowned scientists as keynote speakers and invited speakers, contributed talks at a highly competitive acceptance rate, special issue publications in high-caliber scientific journals, and a broad participation of the research communities serving on the Program Committee and the organizing committees for workshops, tutorials, and posters. The scientific program highlights five themes to provide breadth, depth, and synergy for research collaboration: (1) genomics and molecular structure, function, and evolution; (2) computational systems biology; (3) medical informatics and translational bioinformatics; (4) cross-cutting computational methods and bioinformatics infrastructures, and (5) healthcare informatics, which includes approximately 20 topics.
The paper describes the structure and possible applications of the theory of K-representations (knowledge representations) in bioinformatics and in the development of a Semantic Web of a new generation. It is an original theory of designing semantic-syntactic analyzers of natural language (NL) texts with the broad use of formal means for representing input, intermediary, and output data. The current version of the theory is set forth in a monograph by V. Fomichov (Springer, 2010). The first part of the theory is a formal model describing a system consisting of ten operations on conceptual structures. This model defines a new class of formal languages – the class of SK-languages. The broad possibilities of constructing semantic representations of complex discourses pertaining to biology are shown. A new formal approach to developing multilingual algorithms of semantic-syntactic analysis of NL-texts is outlined. This approach is realized by means of a program in the language PYTHON.
ype II restriction endonucleases and modification DNA-methyltransferases are key instruments of genetic engineering. Recently the number of proteins assigned to this group exceeds 8500. Subtype IIC organizes bifunctional endonuclease-methyltransferase enzymes and currently consists of 16 described members. Here we present phylogenetic tree of 22 new potential bifunctional endonucleases. The majority of them are thought to be fusions of a restriction nuclease with a DNA-methyltransferase and a target recognition subunit of type I restriction-modification systems (R-M-S structure). A RM.AloI isoschizomer from Prevotella copri DSM-18205, PcoI, has been cloned, purified and its REase activity demonstrated. It cuts DNA in magnesium-dependent manner and demonstrates high affinity to DNA, which probably reflects its mechanism of action. This work provides additional proves that gene fusion might play …
This volume covers some of the topics that are related to the rapidly growing field of biomedical informatics. In June 11–12, 2010 a workshop entitled ‘Optimization and Data Analysis in Biomedical Informatics’ was organized at The Fields Institute. Following this event, invited contributions were gathered based on the talks presented at the workshop, and additional invited chapters were solicited from leading experts. In this publication, the authors share their expertise in the form of state-of-the-art research and review chapters, bringing together researchers from different disciplines and emphasizing the value of mathematical methods in the areas of clinical sciences.
A comprehensive theoretical framework for the development of a Semantic Web of a new generation, or of a Multilingual Semantic Web, is outlined. Firstly, the paper grounds the possibility of using a mathematical model being the kernel of the theory of K-representations and describing a system of 10 partial operations on conceptual structures for building semantic representations (or text meaning representations) of, likely, arbitrary sentences and discourses in English, Russian, French, German, and other languages. The possibilities of using SK-languages defined by the theory of K-representations for building semantic annotations of informational sources and for constructing semantic representations of discourses pertaining to biology and medicine are illustrated. Secondly, an original strategy of transforming the existing Web into a Semantic Web of a new generation with the well-developed mechanisms of understanding natural language texts is described. The third subject of this paper is a description of the correspondence between the inputs and outputs of the elaborated algorithm of semantic-syntactic analysis and of its advantages; the semantic representations of the input texts are the expressions of SK-languages (standard knowledge languages). The input texts can be the statements, questions, and commands from the sublanguages of English, Russian, and German. The algorithm has been implemented by means of the programming language PYTHON.
Bioinformatics studies often rely on similarity measures between sequence pairs, which often pose a bottleneck in large-scale sequence analysis.
Here, we present a new convolutional kernel function for protein sequences called the Lempel-Ziv-Welch (LZW)-Kernel. It is based on code words identified with the LZW universal text compressor. The LZW-Kernel is an alignment-free method, it is always symmetric, is positive, always provides 1.0 for self-similarity and it can directly be used with Support Vector Machines (SVMs) in classification problems, contrary to normalized compression distance, which often violates the distance metric properties in practice and requires further techniques to be used with SVMs. The LZW-Kernel is a one-pass algorithm, which makes it particularly plausible for big data applications. Our experimental studies on remote protein homology detection and protein classification tasks reveal that the LZW-Kernel closely approaches the performance of the Local Alignment Kernel (LAK) and the SVM-pairwise method combined with Smith-Waterman (SW) scoring at a fraction of the time. Moreover, the LZW-Kernel outperforms the SVM-pairwise method when combined with Basic Local Alignment Search Tool (BLAST) scores, which indicates that the LZW code words might be a better basis for similarity measures than local alignment approximations found with BLAST. In addition, the LZW-Kernel outperforms n-gram based mismatch kernels, hidden Markov model based SAM and Fisher kernel and protein family based PSI-BLAST, among others. Further advantages include the LZW-Kernel’s reliance on a simple idea, its ease of implementation, and its high speed, three times faster than BLAST and several magnitudes faster than SW or LAK in our tests.
Availability and implementation
LZW-Kernel is implemented as a standalone C code and is a free open-source program distributed under GPLv3 license and can be downloaded from https://github.com/kfattila/LZW-Kernel.
Supplementary data are available at Bioinformatics Online.