scholarly journals New Insights into the Co-Occurrences of Glycoside Hydrolase Genes among Prokaryotic Genomes through Network Analysis

2021 ◽  
Vol 9 (2) ◽  
pp. 427
Author(s):  
Alei Geng ◽  
Meng Jin ◽  
Nana Li ◽  
Daochen Zhu ◽  
Rongrong Xie ◽  
...  
Keyword(s):  
Network Analysis ◽  
Glycoside Hydrolase ◽  
Relevant Information ◽  
Microbial Evolution ◽  
Functional Classification ◽  
Carbohydrate Utilization ◽  
Cazy Database ◽  
Prokaryotic Genomes ◽  
Angle Of View ◽  
Average Gene

Glycoside hydrolase (GH) represents a crucial category of enzymes for carbohydrate utilization in most organisms. A series of glycoside hydrolase families (GHFs) have been classified, with relevant information deposited in the CAZy database. Statistical analysis indicated that most GHFs (134 out of 154) were prone to exist in bacteria rather than archaea, in terms of both occurrence frequencies and average gene numbers. Co-occurrence analysis suggested the existence of strong or moderate-strong correlations among 63 GHFs. A combination of network analysis by Gephi and functional classification among these GHFs demonstrated the presence of 12 functional categories (from group A to L), with which the corresponding microbial collections were subsequently labeled, respectively. Interestingly, a progressive enrichment of particular GHFs was found among several types of microbes, and type-L as well as type-E microbes were deemed as functional intensified species which formed during the microbial evolution process toward efficient decomposition of lignocellulose as well as pectin, respectively. Overall, integrating network analysis and enzymatic functional classification, we were able to provide a new angle of view for GHs from known prokaryotic genomes, and thus this study is likely to guide the selection of GHs and microbes for efficient biomass utilization.

scholarly journals Co-expression networks for plant biology: why and how

2019 ◽  
Vol 51 (10) ◽  
pp. 981-988 ◽  
Author(s):  
Xiaolan Rao ◽  
Richard A Dixon
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Expression Analysis ◽  
Expression Profiling ◽  
Recent Literature ◽  
Genomic Data ◽  
Relevant Information ◽  
Plant Biology ◽  
Biologically Relevant

Abstract Co-expression network analysis is one of the most powerful approaches for interpretation of large transcriptomic datasets. It enables characterization of modules of co-expressed genes that may share biological functional linkages. Such networks provide an initial way to explore functional associations from gene expression profiling and can be applied to various aspects of plant biology. This review presents the applications of co-expression network analysis in plant biology and addresses optimized strategies from the recent literature for performing co-expression analysis on plant biological systems. Additionally, we describe the combined interpretation of co-expression analysis with other genomic data to enhance the generation of biologically relevant information.

scholarly journals Social network analysis and mining: challenges and applications

2021 ◽  
Author(s):  
Bruna P. Fonseca ◽  
Priscila C. Albuquerque ◽  
Fabio Zicker ◽  
Carlos M. Morel
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Practical Knowledge ◽  
Relevant Information ◽  
Critical Perspective ◽  
Research Fields ◽  
New Challenges ◽  
Advanced Computing ◽  
Computing Infrastructure

Social network analysis and mining (SNAM) is a powerful tool to dis- close relevant information hidden in large volumes of raw data. Its application to several research fields, powered by automation and advanced computing infrastructure, expanded its use and brought along new challenges. In this paper, we provide a critical perspective on SNAM’s major challenges, by discussing a few examples. We also address some promising applications that can potentially translate SNAM results into practical knowledge.

scholarly journals Metagenomic analysis reveals rumen microbiota alteration of the yak at different stages of growth

2021 ◽  
Author(s):  
Li Wang ◽  
Li Juan ◽  
Ahmad Aboragah ◽  
Mingfeng Jiang ◽  
Juan J. Loor
Keyword(s):  
Glycoside Hydrolase ◽  
Age Groups ◽  
Carbohydrate Binding ◽  
The Tibetan Plateau ◽  
Tissue Slices ◽  
Rumen Microbiota ◽  
Stages Of Growth ◽  
Ruminant Species ◽  
Cazy Database ◽  
Carbohydrate Binding Modules

Abstract The Yak (Bos grunniens) is a unique ruminant species that is crucially important to agriculture in the Tibetan plateau. Variation of microorganism communities in the yak rumen is of great interest because of possible links to environmentally and economically important traits. In this study, we performed histological and microbial analyses of the yak rumen at 5 stages of growth: 1 day, 20 days, 60 days, 15 months, and 5 years of age. Tissue slices and metagenomics sequencing were used. The rumen index increased gradually from 1 day to 5 years of age. These were significant differences in rumen index between the 60d, 15m, and 5y group (p < 0.05). Compared with other time points, the thickness of muscularis along with length and width of rumen papillae at 60 d,15 m, and 5 years of age increased and differed (p < 0.05), respectively. At the phylum level, Bacteroidetes and Firmicutes were the phyla with the highest abundance in all the age groups. A total of 115,401 genes were annotated on the CAZy database. Glycoside Hydrolase (GH) had the highest relative abundance, followed by Glycosyl Transferase (GT), and Carbohydrate-binding Modules (CBM). There were significant variations for the microbial species and CAZys within the five groups. Taken together, the morphology and microbiota in the yak rumen changed at various stages of growth and likely played a significant role in the absorption of nutrients. This study provides new insights into the function of yak rumen microbiota and physiologic adaptations in plateau animals.

Event synchrony based complex network analysis of heavy precipitation in different monsoon regions revealing dynamical patterns of extreme event formation and propagation

2021 ◽  
Author(s):  
Reik Donner ◽  
Frederik Wolf
Keyword(s):  
Network Analysis ◽  
East Asia ◽  
Summer Monsoon ◽  
Heavy Rainfall ◽  
Spatial Organization ◽  
Extreme Event ◽  
Heavy Precipitation ◽  
Relevant Information ◽  
Extreme Weather Events ◽  
South American

&lt;p&gt;Investigating the synchrony and interdependency of heavy rainfall occurrences across and between different tropical regions offers a new perspective on the underlying physical mechanisms. In this context, studies utilizing functional network representations have recently contributed to significant advances in the understanding and prediction of extreme weather events. Here, we systematically contrast previous results on spatiotemporal extreme precipitation patterns in three key monsoon regions (India, South America and East Asia) based on the concept of event synchronization (ES) with corresponding patterns obtained using the closely related event coincidence analysis (ECA) approach. Our findings demonstrate that an additional window size parameter of ECA not involved in ES allows for a more detailed analysis of the formation and propagation processes associated with heavy precipitation events. While the resulting network connectivity patterns based on both approaches closely resemble each other for the case of the South American monsoon system and the Indian summer monsoon, there exist subtle differences that carry climatologically relevant information. We further exploit the advanced potentials provided by ECA for studying in greater detail the spatial organization of East Asian summer monsoon (EASM) related heavy precipitation across the relevant season in a time-dependent fashion. Our results show that the formation of the Baiu front as a main feature of the EASM is accompanied by a double-band of synchronous heavy rainfall with two spatially dislocated centers north and south of the front. Although these bands are closely related to low- and high-level winds which are commonly assumed to be independent of each other, it is rather their mutual interconnectivity that changes during the different phases of the EASM season in a characteristic way. The thus obtained insights could provide relevant information for improving existing forecasting strategies for monsoon onset and strength.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;References:&lt;/p&gt;&lt;p&gt;Odenweller, R.V. Donner: Disentangling synchrony from serial dependency in paired-event time series. Physical Review E, 101(5), 052213 (2020)&lt;/p&gt;&lt;p&gt;Wolf, J. Bauer, N. Boers, R.V. Donner: Event synchrony measures for functional climate network analysis: A case study on South American rainfall dynamics. Chaos, 30(3), 033102 (2020)&lt;/p&gt;&lt;p&gt;Wolf, U. &amp;#214;zt&amp;#252;rk, K. Cheung, R.V. Donner: Spatiotemporal patterns of synchronous heavy rainfall events in East Asia during the Baiu season. Earth System Dynamics Discussions. doi:10.5194/esd-2020-69 (2020)&lt;/p&gt;&lt;p&gt;Wolf, R.V. Donner: Spatial organization of connectivity in functional climate networks describing event synchrony of heavy precipitation. European Physical Journal Special Topics (in review)&lt;/p&gt;

scholarly journals Adoption of Network Analysis Techniques to Understand the Training Process in Brazil

AWARI ◽  
2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Higor Alexandre Duarte Mascarenhas ◽  
Thiago Magela Rodrigues Dias ◽  
Patrícia Mascarenhas Dias
Keyword(s):  
Network Analysis ◽  
Relevant Information ◽  
Training Process ◽  
High Concentration ◽  
Data Set ◽  
Doctoral Level ◽  
Analysis Techniques ◽  
Brazilian Students ◽  
Level Of Training ◽  
High Level

The migration of Brazilians has become more and more frequent nowadays, with the main purpose of obtaining better living conditions. Studies indicate that one of the main reasons for migration is the search for training at a high level of training. Therefore, in this scenario, this research has as main objective to analyze the exodus of Brazilian students during their academic formation process, from data extracted from their curricula registered in the Lattes Platform with the adoption of network analysis techniques. The Lattes Platform was used for referring to one of the main Brazilian academic repositories, and for having relevant information for this research. Therefore, the LattesDataXplorer framework was used for the extraction and treatment of the data. Subsequently, the data set of individuals with a doctorate completed were selected because they are individuals with a higher level of education and who maintain a constant update of their curricula. Once this was done, data was enriched with geolocation and information from the institutions where they trained, in order to obtain results from distances covered by doctors. As a way of visualizing data, network analysis was used, and metrics were used to obtain an overview of how the Brazilian scientific exodus occurs. A high concentration of doctors is perceived in cities with a higher concentration of universities that have postgraduate programs at the master's and doctoral level, as well as being characterized by having higher incomes per capita.

scholarly journals Cooperative People Tracking by Distributed Cameras Network

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1780
Author(s):  
Yi-Chang Wu ◽  
Ching-Han Chen ◽  
Yao-Te Chiu ◽  
Pi-Wei Chen
Keyword(s):  
Network Architecture ◽  
Relevant Information ◽  
People Tracking ◽  
People Detection ◽  
Camera System ◽  
Narrow Angle ◽  
Detection And Tracking ◽  
Hand Off ◽  
Smooth Tracking ◽  
Angle Of View

In the application of video surveillance, reliable people detection and tracking are always challenging tasks. The conventional single-camera surveillance system may encounter difficulties such as narrow-angle of view and dead space. In this paper, we proposed multi-cameras network architecture with an inter-camera hand-off protocol for cooperative people tracking. We use the YOLO model to detect multiple people in the video scene and incorporate the particle swarm optimization algorithm to track the person movement. When a person leaves the area covered by a camera and enters an area covered by another camera, these cameras can exchange relevant information for uninterrupted tracking. The motion smoothness (MS) metrics is proposed for evaluating the tracking quality of multi-camera networking system. We used a three-camera system for two persons tracking in overlapping scene for experimental evaluation. Most tracking person offsets at different frames were lower than 30 pixels. Only 0.15% of the frames showed abrupt increases in offsets pixel. The experiment results reveal that our multi-camera system achieves robust, smooth tracking performance.

Social network analysis for farmers' hearing services in a rural community

2010 ◽  
Vol 16 (1) ◽  
pp. 47 ◽  
Author(s):  
Tony Lower ◽  
Lyn Fragar ◽  
Julie Depcynzksi ◽  
Jeffrey Fuller ◽  
Kathy Challinor ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Health Service ◽  
Service Provision ◽  
Relevant Information ◽  
Health Networks ◽  
Health Service Provision ◽  
Hearing Health ◽  
Farming Families

This study aimed to define current hearing health service networks for farming families in a major regional centre in New South Wales, in order to identify approaches that can strengthen local service provision. A pilot survey of individuals and agencies that potentially work with farmers was undertaken and a social network analysis completed to assess the self-reported links of agencies with each other. Thirteen agencies with a role in hearing health service provision participated with results indicating that nurse audiometrists, WorkCover NSW and agricultural retailers have the lead role in disseminating relevant information within the network. For client referrals the nurse audiometrist, private audiometry services, general practitioners, ear, nose and throat specialists and industry groups played the major roles. Social network analysis can assist in defining hearing health networks and can be used to highlight potential actions that can strengthen networks to enhance services for farmers and their families.

scholarly journals A Qualitative Analysis of a Team Fortress 2 Social Network

2018 ◽  
Author(s):  
Ilan Tollman ◽  
Motty Yaffe
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Qualitative Analysis ◽  
Online Social Network ◽  
Computer Game ◽  
Relevant Information ◽  
Social Consequence ◽  
Academic Field ◽  
Gaming Culture

The Gaming Industry is one of the most dynamic and fasted growing of our time, from the arcade culture to the widespread integration of household gaming consoles and home gaming PCs, whose steadily rising popularity, performance and inter-connectivity is allowing for more and more growth in the range and permeability of gaming and gaming culture. With its widespread popularity and its ever-increasing influence, through the acceptance of gaming culture as mainstream, the gaming world is becoming a crucial field of study for better understanding of online communities and social interaction. In this paper we will expand on the academic field of Online Social Network Analysis through the examination of a selected social network from the gaming world as a microcosm of online social interactions. The paper will draw on Social Network Analysis, Sociology and Communications theories to further expand the understanding of on-line interactions on a network scale. Current gaming focused research leads in two main directions, social consequence whether they be pro social or anti social. There is also however a smaller developing trend of study within the Social Network Analysis field that uses the data collected by computer game makers to study network structure as a variable of its own. In this research the findings of this trend within the computer game research will be used to conduct a qualitative Analysis of a small friends list network from Team Fortress 2. The data collected will compared and contrasted with established Sociology and Communications theories, the expected results and variances will then be explained using the findings of Social Network Analysis research.The Research draws the Two Step Flow communications theory (Lazarsfeld, 1948), and a slightly more refined version of the theory (Katz, 1957), to deduce relevant information on the interaction between companies, hardcore gamers and more casual gamers. The study will also draw predominantly on Mark Granovette work on Social Network Analysis.

scholarly journals Predicted Highly Expressed Genes of Diverse Prokaryotic Genomes

2000 ◽  
Vol 182 (18) ◽  
pp. 5238-5250 ◽  
Author(s):  
Samuel Karlin ◽  
Jan Mrázek
Keyword(s):  
Codon Usage ◽  
Ribosomal Proteins ◽  
Deinococcus Radiodurans ◽  
Tricarboxylic Acid Cycle ◽  
Ribosomal Protein Genes ◽  
Expression Levels ◽  
Prokaryotic Genomes ◽  
Highly Expressed Genes ◽  
Average Gene ◽  
Processing Factors

ABSTRACT Our approach in predicting gene expression levels relates to codon usage differences among gene classes. In prokaryotic genomes, genes that deviate strongly in codon usage from the average gene but are sufficiently similar in codon usage to ribosomal protein genes, to translation and transcription processing factors, and to chaperone-degradation proteins are predicted highly expressed (PHX). By these criteria, PHX genes in most prokaryotic genomes include those encoding ribosomal proteins, translation and transcription processing factors, and chaperone proteins and genes of principal energy metabolism. In particular, for the fast-growing speciesEscherichia coli, Vibrio cholerae,Bacillus subtilis, and Haemophilus influenzae, major glycolysis and tricarboxylic acid cycle genes are PHX. InSynechocystis, prime genes of photosynthesis are PHX, and in methanogens, PHX genes include those essential for methanogenesis. Overall, the three protein families—ribosomal proteins, protein synthesis factors, and chaperone complexes—are needed at many stages of the life cycle, and apparently bacteria have evolved codon usage to maintain appropriate growth, stability, and plasticity. New interpretations of the capacity of Deinococcus radioduransfor resistance to high doses of ionizing radiation is based on an excess of PHX chaperone-degradation genes and detoxification genes. Expression levels of selected classes of genes, including those for flagella, electron transport, detoxification, histidine kinases, and others, are analyzed. Flagellar PHX genes are conspicuous among spirochete genomes. PHX genes are positively correlated with strong Shine-Dalgarno signal sequences. Specific regulatory proteins, e.g., two-component sensor proteins, are rarely PHX. Genes involved in pathways for the synthesis of vitamins record low predicted expression levels. Several distinctive PHX genes of the available complete prokaryotic genomes are highlighted. Relationships of PHX genes with stoichiometry, multifunctionality, and operon structures are discussed. Our methodology may be used complementary to experimental expression analysis.

scholarly journals Probe-mining of endo-1,4-beta-xylanase from goats-rumen bacterial metagenomic DNA data

2021 ◽  
Vol 19 (3) ◽  
pp. 519-528
Author(s):  
Dao Trong Khoa ◽  
Do Thi Huyen ◽  
Truong Nam Hai
Keyword(s):  
Glycoside Hydrolase ◽  
Xylanase Activity ◽  
Experimental Studies ◽  
Open Reading Frames ◽  
Kegg Database ◽  
Metagenomic Dna ◽  
Maximum Score ◽  
Online Databases ◽  
Cazy Database ◽  
Reading Frames

Endo-1,4-beta-xylanases (xylanases) are classified into 9 glycoside hydrolase families, GH5, 8, 10, 11, 30, 43, 51, 98, and 141 based on the CAZy database. The probe sequences representing the enzymes were constructed from published sequences of actual experimental studies with xylan decomposition activity. From online databases, we found one sequence belonging to the GH5 family, 6 sequences belonging to the GH8 family and 5 sequences belonging to the GH30 family exhibiting xylanase activity. Thus specific probes for xylanase GH8 and GH30 families were designed with the length of 351 and 425 amino acids respectively. The reference values for the probe of the GH8 family were defined as the sequences with maximum score greater than 168, the lowest coverage was 84%, the lowest similarity was 36%; for the probe GH30, the maximum score was greater than 316, the coverage was greater than 98%, the similarity was greater than 41%. Using the built probes, including the probe of the two GH10 and GH11 families, we found 41 xylanase-encoding sequences from the metagenomic DNA data of bacteria in Vietnamese goats’rumen. Of the 41 exploited sequences, 19 were identical to the BGI company's annotation result based on KEGG database, whereas there were 16 sequences that are not annotated by the BGI company. Total 28 of 41 exploited sequences were complete open reading frames, of which the predicted ternary structure was highly similar to the published structures of xylanase.

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