InsectOR – webserver for sensitive identification of insect olfactory receptor genes from non-model genomes

Insect Olfactory Receptors (ORs) are diverse family of membrane protein receptors responsible for most of the insect olfactory perception and communication, and hence they are of utmost importance for developing repellents or pesticides. Accurate gene prediction of insect ORs from newly sequenced genomes is an important but challenging task. We have developed a dedicated webserver, ‘insectOR’, to predict and validate insect OR genes using multiple gene prediction algorithms, accompanied by relevant validations. It is possible to employ this server nearly automatically and perform rapid prediction of the OR gene loci from thousands of OR-protein-to-genome alignments, resolve gene boundaries for tandem OR genes and refine them further to provide more complete OR gene models. InsectOR outperformed the popular genome annotation pipelines (MAKER and NCBI eukaryotic genome annotation) in terms of overall sensitivity at base, exon and locus level, when tested on two distantly related insect genomes. It displayed more than 95% nucleotide level precision in both tests. Finally, given the same input data and parameters, InsectOR missed less than 2% gene loci, in contrast to 55% loci missed by MAKER for Drosophila melanogaster. The webserver is freely available on the web at http://caps.ncbs.res.in/insectOR/ and the basic package can be downloaded from https://github.com/sdk15/insectOR for local use. This tool will allow biologists to perform quick preliminary identification of insect olfactory receptor genes from newly sequenced genomes and also assist in their further detailed annotation. Its usage can also be extended to other divergent gene families.

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A unified nomenclature for vertebrate olfactory receptors

10.21203/rs.2.14887/v2 ◽

2020 ◽

Author(s):

Tsviya Olender ◽

Tamsin E.M. Jones ◽

Elspeth Bruford ◽

Doron Lancet

Keyword(s):

Receptor Gene ◽

Olfactory Receptors ◽

Large Deletion ◽

Ecological Niches ◽

Gene Nomenclature ◽

Nomenclature System ◽

Or Gene ◽

Species Specific ◽

Or Genes ◽

Genomic Cluster

Abstract Background Olfactory receptors (ORs) are G protein-coupled receptors with a crucial role in odor detection. A typical mammalian genome harbors ~1000 OR genes and pseudogenes; however, different gene duplication/deletion events have occurred in each species, resulting in complex orthology relationships. While the human OR nomenclature is widely accepted and based on phylogenetic classification into 18 families and further into subfamilies, for other mammals different and multiple nomenclature systems are currently in use, thus concealing important evolutionary and functional insights. Results Here we describe the Mutual Maximum Similarity (MMS) algorithm, a systematic classifier for assigning a human-centric nomenclature to any OR gene based on inter-species hierarchical pairwise similarities. MMS was applied to the OR repertoires of seven mammals and zebrafish. Altogether, we assigned symbols to 10,249 ORs. This nomenclature is supported by both phylogenetic and synteny analyses. The availability of a unified nomenclature provides a framework for diverse studies, where textual symbol comparison allows immediate identification of potential ortholog groups as well as species-specific expansions/deletions; for example, Or52e5 and Or52e5b represent a rat-specific duplication of OR52E5 . Another example is the complete absence of OR subfamily OR6Z among primate OR symbols. In other mammals, OR6Z members are located in one genomic cluster, suggesting a large deletion in the great ape lineage. An additional 14 mammalian OR subfamilies are missing from the primate genomes. While in chimpanzee 87% of the symbols were identical to human symbols, this number decreased to ~50% in dog and cow and to ~30% in rodents, reflecting the adaptive changes of the OR gene superfamily across diverse ecological niches. Application of the proposed nomenclature to zebrafish revealed similarity to mammalian ORs that could not be detected from the current zebrafish olfactory receptor gene nomenclature. Conclusions We have consolidated a unified standard nomenclature system for the vertebrate OR superfamily. The new nomenclature system will be applied to cow, horse, dog and chimpanzee by the Vertebrate Gene Nomenclature Committee and its implementation is currently under consideration by other relevant species-specific nomenclature committees.

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A unified nomenclature for vertebrate olfactory receptors

10.21203/rs.2.14887/v1 ◽

2019 ◽

Author(s):

Tsviya Olender ◽

Tamsin E.M. Jones ◽

Michal Twik ◽

Elspeth Bruford ◽

Doron Lancet

Keyword(s):

Receptor Gene ◽

Olfactory Receptors ◽

Large Deletion ◽

Ecological Niches ◽

Gene Nomenclature ◽

Nomenclature System ◽

Or Gene ◽

Species Specific ◽

Or Genes ◽

Genomic Cluster

Abstract Background Olfactory receptors (ORs) are G protein-coupled receptors with a crucial role in odor detection. A typical mammalian genome harbors ~1000 OR genes and pseudogenes; however, different gene duplication/deletion events have occurred in each species, resulting in complex orthology relationships. While the human OR nomenclature is widely accepted and based on phylogenetic classification into 18 families and further into subfamilies, for other mammals different and multiple nomenclature systems are currently in use, thus concealing important evolutionary and functional insights. Results Here we describe the Mutual Maximum Similarity (MMS) algorithm, a systematic classifier for assigning a human-centric nomenclature to any OR gene based on inter-species hierarchical pairwise similarities. MMS was applied to the OR repertoires of seven mammals and zebrafish. Altogether, we assigned symbols to 10,249 ORs. This nomenclature is supported by both phylogenetic and synteny analyses. The availability of a unified nomenclature provides a framework for diverse studies, where textual symbol comparison allows immediate identification of potential ortholog groups as well as species-specific expansions/deletions; for example, Or52e5 and Or52e5b represent a rat-specific duplication of OR52E5 . Another example is the complete absence of OR subfamily OR6Z among primate OR symbols. In other mammals, OR6Z members are located in one genomic cluster, suggesting a large deletion in the great ape lineage. An additional 14 mammalian OR subfamilies are missing from the primate genomes. While in chimpanzee 87% of the symbols were identical to human symbols, this number decreased to ~50% in dog and cow and to ~30% in rodents, reflecting the adaptive changes of the OR gene superfamily across diverse ecological niches. Application of the proposed nomenclature to zebrafish revealed similarity to mammalian ORs that could not be detected from the current zebrafish olfactory receptor gene nomenclature. Conclusions We have consolidated a unified standard nomenclature system for the vertebrate OR superfamily. The new nomenclature system will be applied to cow, horse, dog and chimpanzee by the Vertebrate Gene Nomenclature Committee and its implementation is currently under consideration by other relevant species-specific nomenclature committees.

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APLIKASI PENCARI INFORMASI PERMINTAAN LAYANAN WEB YANG ERROR MENGGUNAKAN ALGORITMA BOYER-MOORE

Unes journal of Information System ◽

10.31933/ujis.1.1.001-010.2016 ◽

2016 ◽

Vol 1 (1) ◽

pp. 001

Author(s):

Harry Setya Hadi

Keyword(s):

Data Storage ◽

Computer Network ◽

Web Server ◽

Access Methods ◽

Ip Address ◽

String Searching ◽

Common Process ◽

Web Server Logs ◽

Different Parts ◽

The Web

String searching is a common process in the processes that made the computer because the text is the main form of data storage. Boyer-Moore is the search string from right to left is considered the most efficient methods in practice, and matching string from the specified direction specifically an algorithm that has the best results theoretically. A system that is connected to a computer network that literally pick a web server that is accessed by multiple users in different parts of both good and bad aim. Any activity performed by the user, will be stored in Web server logs. With a log report contained in the web server can help a web server administrator to search the web request error. Web server log is a record of the activities of a web site that contains the data associated with the IP address, time of access, the page is opened, activities, and access methods. The amount of data contained in the resulting log is a log shed useful information.

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SSMBS: a web server to locate sequentially separated motifs in biological sequences

Journal of Applied Crystallography ◽

10.1107/s0021889809047050 ◽

2009 ◽

Vol 43 (1) ◽

pp. 203-205 ◽

Cited By ~ 1

Author(s):

Chetan Kumar ◽

K. Sekar

Keyword(s):

Amino Acids ◽

Web Server ◽

Nucleotide Sequences ◽

Regular Expressions ◽

Biological Sequences ◽

Sequence Motifs ◽

Specific Order ◽

The Web

The identification of sequence (amino acids or nucleotides) motifs in a particular order in biological sequences has proved to be of interest. This paper describes a computing server,SSMBS, which can locate and display the occurrences of user-defined biologically important sequence motifs (a maximum of five) present in a specific order in protein and nucleotide sequences. While the server can efficiently locate motifs specified using regular expressions, it can also find occurrences of long and complex motifs. The computation is carried out by an algorithm developed using the concepts of quantifiers in regular expressions. The web server is available to users around the clock at http://dicsoft1.physics.iisc.ernet.in/ssmbs/.

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Setting Up the Web Server and Database Environment

Building Database-Driven Flash Applications ◽

10.1007/978-1-4302-1112-9_2 ◽

2004 ◽

pp. 53-92

Author(s):

Noel Jerke ◽

Darin Beard

Keyword(s):

Web Server ◽

The Web

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Organization and distribution of glomeruli in the bowhead whale olfactory bulb

10.7287/peerj.preprints.740 ◽

2014 ◽

Author(s):

Takushi Kishida ◽

J. G. M. Thewissen ◽

Sharon Usip ◽

John C George ◽

Robert S Suydam

Keyword(s):

Olfactory Bulb ◽

Olfactory Receptor ◽

Olfactory Receptors ◽

Molecular Data ◽

Dorsal Side ◽

Bowhead Whale ◽

Model Organisms ◽

Marker Genes ◽

Baleen Whales ◽

Olfactory Receptor Genes

Although modern baleen whales still possess a functional olfactory systems that includes olfactory bulbs, cranial nerve I and olfactory receptor genes, their olfactory capabilities have been reduced profoundly. This is probably in response to their fully aquatic lifestyle. The glomeruli that occur in the olfactory bulb can be divided into two non-overlapping domains, a dorsal domain and a ventral domain. Recent molecular studies revealed that all modern whales have lost olfactory receptor genes and marker genes that are specific to the dorsal domain, and that a modern baleen whale possess only 60 olfactory receptor genes. Here we show that olfactory bulb of bowhead whales (Balaena mysticetus, Mysticeti) lacks glomeruli on the dorsal side, consistent with the molecular data. In addition, we estimate that there are more than 4,000 glomeruli in the bowhead whale olfactory bulb. Olfactory sensory neurons that express the same olfactory receptor in mice generally project to two specific glomeruli in an olfactory bulb, meaning that ratio of the number of olfactory receptors : the number of glomeruli is approximately 1:2. However, we show here that this ratio is not applicable to whales, indicating the limitation of mice as model organisms for understanding the initial coding of odor information among mammals.

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User’s Behaviour inside a Digital Library

Data Mining ◽

10.4018/978-1-4666-2455-9.ch067 ◽

2013 ◽

pp. 1312-1319

Author(s):

Marco Scarnò

Keyword(s):

Data Mining ◽

Digital Library ◽

Web Mining ◽

Dynamic Change ◽

Web Server ◽

Scientific Field ◽

Data Mining Techniques ◽

Log File ◽

The Web ◽

The Way

CASPUR allows many academic Italian institutions located in the Centre-South of Italy to access more than 7 million articles through a digital library platform. The behaviour of its users were analyzed by considering their “traces”, which are stored in the web server log file. Using several web mining and data mining techniques the author discovered a gradual and dynamic change in the way articles are accessed. In particular there is evidence of a journal browsing increase in comparison to the searching mode. Such phenomenon were interpreted using the idea that browsing better meets the needs of users when they want to keep abreast about the latest advances in their scientific field, in comparison to a more generic searching inside the digital library.

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Web Server Performance Improvement Using Dynamic Load Balancing Techniques: A Review

Asian Journal of Research in Computer Science ◽

10.9734/ajrcos/2021/v10i130234 ◽

2021 ◽

pp. 47-62

Author(s):

Ibrahim Mahmood Ibrahim ◽

Siddeeq Y. Ameen ◽

Hajar Maseeh Yasin ◽

Naaman Omar ◽

Shakir Fattah Kak ◽

...

Keyword(s):

Load Balancing ◽

Response Time ◽

Performance Improvement ◽

Web Server ◽

Dynamic Load Balancing ◽

The Internet ◽

Web Servers ◽

Web Server Performance ◽

Server Clusters ◽

The Web

Today, web services rapidly increased and are accessed by many users, leading to massive traffic on the Internet. Hence, the web server suffers from this problem, and it becomes challenging to manage the total traffic with growing users. It will be overloaded and show response time and bottleneck, so this massive traffic must be shared among several servers. Therefore, the load balancing technologies and server clusters are potent methods for dealing with server bottlenecks. Load balancing techniques distribute the load among servers in the cluster so that it balances all web servers. The motivation of this paper is to give an overview of the several load balancing techniques used to enhance the efficiency of web servers in terms of response time, throughput, and resource utilization. Different algorithms are addressed by researchers and get good results like the pending job, and IP hash algorithms achieve better performance.

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MHC-Linked Olfactory Receptor Loci Exhibit Polymorphism and Contribute to Extended HLA/OR-Haplotypes

Genome Research ◽

10.1101/gr.120400 ◽

2000 ◽

Vol 10 (12) ◽

pp. 1968-1978 ◽

Cited By ~ 1

Author(s):

Anke Ehlers ◽

Stephan Beck ◽

Simon A. Forbes ◽

John Trowsdale ◽

Armin Volz ◽

...

Keyword(s):

Olfactory Receptor ◽

Sequence Data ◽

Allelic Variation ◽

Mate Preferences ◽

Coding Region ◽

Link Type ◽

Or Gene ◽

Hla Haplotypes ◽

A Minor ◽

Or Genes

Clusters of olfactory receptor (OR) genes are found on most human chromosomes. They are one of the largest mammalian multigene families. Here, we report a systematic study of polymorphism of OR genes belonging to the largest fully sequenced OR cluster. The cluster contains 36 OR genes, of which two belong to the vomeronasal 1 (V1-OR) family. The cluster is divided into a major and a minor region at the telomeric end of the HLA complex on chromosome 6. These OR genes could be involved in MHC-related mate preferences. The polymorphism screen was carried out with 13 genes from the HLA-linked OR cluster and three genes from chromosomes 7, 17, and 19 as controls. Ten human cell lines, representing 18 different chromosome 6s, were analyzed. They were from various ethnic origins and exhibited different HLA haplotypes. All OR genes tested, including those not linked to the HLA complex, were polymorphic. These polymorphisms were dispersed along the coding region and resulted in up to seven alleles for a given OR gene. Three polymorphisms resulted either in stop codons (genes hs6M1-4P,hs6M1-17) or in a 16–bp deletion (gene hs6M1-19P), possibly leading to lack of ligand recognition by the respective receptors in the cell line donors. In total, 13 HLA-linked OR haplotypes could be defined. Therefore, allelic variation appears to be a general feature of human OR genes.[The sequence data reported in this paper have been submitted to EMBL under accession nos. AC006137, AC004178, AJ132194, AL022727, AL031983,AL035402, AL035542, Z98744, CAB55431, AL050339, AL035402, AL096770,AL133267, AL121944, Z98745, AL021808, and AL021807.]

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