Cotranslational folding of proteins on the ribosome.

Many proteins in the cell fold cotranslationally within the restricted space of the polypeptide exit tunnel or at the surface of the ribosome. A growing body of evidence suggests that the ribosome can alter the folding trajectory in many different ways. In this review, we summarize the recent examples of how translation affects folding of single-domain, multiple-domain and oligomeric proteins. The vectorial nature of translation, the spatial constraints of the exit tunnel, and the electrostatic properties of the ribosome-nascent peptide complex define the onset of early folding events. The ribosome can facilitate protein compaction, induce the formation of intermediates that are not observed in solution, or delay the onset of folding. Examples of single-domain proteins suggest that early compaction events can define the folding pathway for some types of domain structures. Folding of multi-domain proteins proceeds in a domain-wise fashion, with each domain having its role in stabilizing or destabilizing neighboring domains. Finally, the assembly of protein complexes can also begin cotranslationally. In all these cases, the ribosome helps the nascent protein to attain a native fold and avoid the kinetic traps of misfolding

Language Learning Motivation Theory and Its Role in the Contecst of Language Teaching Practice in Uzbekistan

The issue of foreign language learning and teaching is almost the most discussed topic in the sphere of andragogy and higher educational system, as it is included into the syllabi of all courses in all higher educational institutions in Uzbekistan. Teaching foreign languages to the students majoring non language specialties always faces the problem of student’s inadequate attitude to the subject as it is not considered to be a core subject. Here is why, the theory of language learning motivation and its role in teaching foreign languages deserves a diverse attention of the specialists.  This article discusses these issues and some practical survey results dedicated to the topic being discussed

Invariant Solutions of the Two-Dimensional Shallow Water Equations with a Particular Class of Bottoms

The two-dimensional shallow water equations with a particular bottom and the Coriolis's force $f=f_{0}+\Omega y$ are studied in this paper. The main goal of the paper is to describe all invariant solutions for which the reduced system is a system of ordinary differential equations. For solving the systems of ordinary differential equations we use the sixth-order Runge-Kutta method.Comment: 7 pages, 9 figures, Submitted to AIP Conference Proceedings 2164, 050003 (2019

On parameterized complexity of the Multi-MCS problem

AbstractWe introduce the maximum common subgraph problem for multiple graphs (Multi-MCS) inspired by various biological applications such as multiple alignments of gene sequences, protein structures, metabolic pathways, or protein–protein interaction networks. Multi-MCS is a generalization of the two-graph Maximum Common Subgraph problem (MCS). On the basis of the framework of parameterized complexity theory, we derive the parameterized complexity of Multi-MCS for various parameters for different classes of graphs. For example, for directed graphs with labeled vertices, we prove that the parameterized m-Multi-MCS problem is W[2]-hard, while the parameterized k-Multi-MCS problem is W[t]-hard (∀t≥1), where m and k are the size of the maximum common subgraph and the number of multiple graphs, respectively. We show similar results for other parameterized versions of the Multi-MCS problem for directed graphs with vertex labels and undirected graphs with vertex and edge labels by giving linear FPT reductions of the problems from parameterized versions of the longest common subsequence problem. Likewise, for unlabeled undirected graphs, we show that a parameterized version of the Multi-MCS problem with a fixed number of input graphs is W[1]-complete by showing a linear FPT reduction to and from a parameterized version of the maximum clique problem

Translational control by ribosome pausing in bacteria: How a non-uniform pace of translation affects protein production and folding

Protein homeostasis of bacterial cells is maintained by coordinated processes of protein production, folding, and degradation. Translational efficiency of a given mRNA depends on how often the ribosomes initiate synthesis of a new polypeptide and how quickly they read the coding sequence to produce a full-length protein. The pace of ribosomes along the mRNA is not uniform: periods of rapid synthesis are separated by pauses. Here, we summarize recent evidence on how ribosome pausing affects translational efficiency and protein folding. We discuss the factors that slow down translation elongation and affect the quality of the newly synthesized protein. Ribosome pausing emerges as important factor contributing to the regulatory programs that ensure the quality of the proteome and integrate the cellular and environmental cues into regulatory circuits of the cell

Learning Contextual Embeddings for Knowledge Graph Completion

Knowledge Graphs capture entities and their relationships. However, many knowledge graphs are afflicted by missing data. Recently, embedding methods have been used to alleviate this issue via knowledge graph completion. However, most existing methods only consider the relationship in triples, even though contextual relation types, consisting of the surrounding relation types of a triple, can substantially improve prediction accuracy. Therefore, we propose a contextual embedding method that learns the embeddings of entities and predicates while taking contextual relation types into account. The main benefits of our approach are: (1) improved scalability via a reduced number of epochs needed to achieve comparable or better results with the same memory complexity, (2) higher prediction accuracy (an average of 14%) compared to the related algorithms, and (3) high accuracy for both missing entity and predicate predictions. The source code and the YAGO43k dataset of this paper can be found from (https://github.ncsu.edu/cmoon2/kg)

WebBANC: Building Semantically-Rich Annotated Corpora from Web User Annotations of Minority Languages

Proceedings of the 17th Nordic Conference of Computational Linguistics NODALIDA 2009. Editors: Kristiina Jokinen and Eckhard Bick. NEALT Proceedings Series, Vol. 4 (2009), 48-56. © 2009 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/9206

Global alignment of pairwise protein interaction networks for maximal common conserved patterns

A number of tools for the alignment of protein-protein interaction (PPI) networks have laid the foundation for PPI network analysis. Most of alignment tools focus on finding conserved interaction regions across the PPI networks through either local or global mapping of similar sequences. Researchers are still trying to improve the speed, scalability, and accuracy of network alignment. In view of this, we introduce a connected-components based fast algorithm, HopeMap, for network alignment. Observing that the size of true orthologs across species is small comparing to the total number of proteins in all species, we take a different approach based on a precompiled list of homologs identified by KO terms. Applying this approach to S. cerevisiae (yeast) and D. melanogaster (fly), E. coli K12 and S. typhimurium, E. coli K12 and C. crescenttus, we analyze all clusters identified in the alignment. The results are evaluated through up-to-date known gene annotations, gene ontology (GO), and KEGG ortholog groups (KO). Comparing to existing tools, our approach is fast with linear computational cost, highly accurate in terms of KO and GO terms specificity and sensitivity, and can be extended to multiple alignments easily