scholarly journals DoOR 2.0 - Comprehensive Mapping ofDrosophila melanogasterOdorant Responses

2015 ◽  
Author(s):  
Daniel Muench ◽  
C. Giovanni Galizia
Keyword(s):  
Open Source ◽  
Sensory Neurons ◽  
Response Spectrum ◽  
Odorant Receptors ◽  
Response Matrix ◽  
Web Interface ◽  
Response Data ◽  
Data Points ◽  
Response Profiles ◽  
Comprehensive Mapping

Odors elicit complex patterns of activated olfactory sensory neurons. Knowing the complete olfactome, i.e. responses in all sensory neurons for all odorants, is desirable to understand olfactory coding. The DoOR project combines all availableDrosophilaodorant response data into a single consensus response matrix. Since its first release many studies were published: receptors were deorphanized and several response profiles were expanded. In this study, we add to the odor-response profiles for four odorant receptors (Or10a, Or42b, Or47b, Or56a). We deorphanize Or69a, showing a broad response spectrum with the best ligands including 3-hydroxyhexanoate, alpha-terpineol, 3-octanol and linalool. We include these datasets into DoOR, and provide a comprehensive update of both code and data. The DoOR project has a web interface for quick queries (http://neuro.uni.kn/DoOR), and a downloadable, open source toolbox written in R, including all processed and original datasets. DoOR now gives reliable odorant-responses for nearly allDrosophilaolfactory responding units, listing 693 odorants, for a total of 7381 data points.

IMPLEMENTATION OF MACHINE LEARNING FOR PREDICTING MAIZE CROP YIELDS USING MULTIPLE LINEAR REGRESSION AND BACKWARD ELIMINATION

2021 ◽  
Vol 6 (1) ◽  
pp. 679
Author(s):  
Stephen Fashoto ◽  
Elliot Mbunge ◽  
Gabriel Ogunleye ◽  
Johan Van den Burg
Keyword(s):  
Machine Learning ◽  
Food Security ◽  
Open Source ◽  
Crop Yields ◽  
Local Data ◽  
Maize Crop ◽  
Response Data ◽  
Backward Elimination ◽  
Single Attribute ◽  
Data Points

Predicting maize crop yields especially in maize production is paramount in order to alleviate poverty and contribute towards food security. Many regions experience food shortage especially in Africa because of uncertain climatic changes, poor irrigation facilities, reduction in soil fertility and traditional farming techniques. Therefore, predicting maize crop yields helps policymakers to make timely import and export decisions to strengthen national food security. However, none of the published work has been done to predict maize crop yields using machine learning in Eswatini, Africa. This paper aimed at applying machine learning (ML) to predict maize yields for a single season in Eswatini. A ML model was trained and tested using open-source data and local data. This is done by using three different data splits with the open-source predictor data consisting of 48 data points each with 7 attributes and open-source response data consisting of 48 data points each with a single attribute, adjusted R² values were 0.784 (at 70:30), 0.849 (at 80:20), and 0.878 (at 90:10) before being normalized, 1.00 across the board after normalization, and 0.846 (at 70:30), 0.886 (at 80:20), and 0.885 (at 90:10) after backward elimination. At the second attempt, it is done by using the combined predictor data of 68 data points with 7 attributes each and combined response data of 68 data points with a single attribute each, with the same data splits and methods adjusted R² values were 0.966 (at 70:30), 0.972 (at 80:20), and 0.978 (at 90:10) before being normalized, 1.00 across the board after normalization, and 0.967 (at 70:30), 0.973 (at 80:20), and 0.978 (at 90:10) after backward elimination.      

scholarly journals G protein-coupled odorant receptors underlie mechanosensitivity in mammalian olfactory sensory neurons

2014 ◽  
Vol 112 (2) ◽  
pp. 590-595 ◽  
Author(s):  
Timothy Connelly ◽  
Yiqun Yu ◽  
Xavier Grosmaitre ◽  
Jue Wang ◽  
Lindsey C. Santarelli ◽  
...  
Keyword(s):  
G Protein ◽  
Sensory Neurons ◽  
Ectopic Expression ◽  
Host Cells ◽  
Odorant Receptors ◽  
Olfactory Sensory Neurons ◽  
Mechanical Stimuli ◽  
Genetic Ablation ◽  
Mechanical Responses ◽  
G Protein Coupled

Mechanosensitive cells are essential for organisms to sense the external and internal environments, and a variety of molecules have been implicated as mechanical sensors. Here we report that odorant receptors (ORs), a large family of G protein-coupled receptors, underlie the responses to both chemical and mechanical stimuli in mouse olfactory sensory neurons (OSNs). Genetic ablation of key signaling proteins in odor transduction or disruption of OR–G protein coupling eliminates mechanical responses. Curiously, OSNs expressing different OR types display significantly different responses to mechanical stimuli. Genetic swap of putatively mechanosensitive ORs abolishes or reduces mechanical responses of OSNs. Furthermore, ectopic expression of an OR restores mechanosensitivity in loss-of-function OSNs. Lastly, heterologous expression of an OR confers mechanosensitivity to its host cells. These results indicate that certain ORs are both necessary and sufficient to cause mechanical responses, revealing a previously unidentified mechanism for mechanotransduction.

Program for Computation of Response Data from Five Different Gas Chromatograph Detectors Operating Simultaneously

1978 ◽  
Vol 61 (1) ◽  
pp. 18-25
Author(s):  
Harry A Mcleod ◽  
David Lewis
Keyword(s):  
Gas Chromatograph ◽  
Internal Standards ◽  
Baseline Drift ◽  
Response Data ◽  
Flame Ionization ◽  
Relative Retention ◽  
Data Points ◽  
Peak Areas ◽  
Smoothing Procedure ◽  
Spurious Signals

Abstract A novel digital computer program for evaluating data from a gas chromatograph with 5 different detectors—electron capture, flame ionization, nitrogen, phosphorus, and sulfur—operating simultaneously is described. Detector signals are recorded on a 9-channel incremental tape, and then processed off-line by using a NOVA 8K computer system. Spurious signals from each detector are minimized by applying a simplified least squares smoothing procedure to the raw data points. Peak detection logic operating parameters may be varied for each detector. Relative retention times are calculated for 2 internal standards as references and peak areas are corrected for baseline drift. Operator interaction is maximal and several different data reporting formats are used to tabulate the raw and processed data.

scholarly journals Expression Patterns of Odorant Receptors and Response Properties of Olfactory Sensory Neurons in Aged Mice

2009 ◽  
Vol 34 (8) ◽  
pp. 695-703 ◽  
Author(s):  
Anderson C. Lee ◽  
Huikai Tian ◽  
Xavier Grosmaitre ◽  
Minghong Ma
Keyword(s):  
Sensory Neurons ◽  
Expression Patterns ◽  
Odorant Receptors ◽  
Olfactory Sensory Neurons ◽  
Response Properties ◽  
Aged Mice

Molecular Biology of Vertebrate Olfactory Receptors and Circuits

2021 ◽  
Author(s):  
Richard P. Tucker ◽  
Qizhi Gong
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Olfactory Bulb ◽  
Gene Family ◽  
Sensory Neuron ◽  
Sensory Neurons ◽  
Odorant Receptor ◽  
Vomeronasal Organ ◽  
Odorant Receptors ◽  
The Central Nervous System

Animals use their olfactory system for the procurement of food, the detection of danger, and the identification of potential mates. In vertebrates, the olfactory sensory neuron has a single apical dendrite that is exposed to the environment and a single basal axon that projects to the central nervous system (i.e., the olfactory bulb). The first odorant receptors to be discovered belong to an enormous gene family encoding G protein-coupled seven transmembrane domain proteins. Odorant binding to these classical odorant receptors initiates a GTP-dependent signaling cascade that uses cAMP as a second messenger. Subsequently, additional types of odorant receptors using different signaling pathways have been identified. While most olfactory sensory neurons are found in the olfactory sensory neuroepithelium, others are found in specialized olfactory subsystems. In rodents, the vomeronasal organ contains neurons that recognize pheromones, the septal organ recognizes odorant and mechanical stimuli, and the neurons of the Grüneberg ganglion are sensitive to cool temperatures and certain volatile alarm signals. Within the olfactory sensory neuroepithelium, each sensory neuron expresses a single odorant receptor gene out of the large gene family; the axons of sensory neurons expressing the same odorant receptor typically converge onto a pair of glomeruli at the periphery of the olfactory bulb. This results in the transformation of olfactory information into a spatially organized odortopic map in the olfactory bulb. The axons originating from the vomeronasal organ project to the accessory olfactory bulb, whereas the axons from neurons in the Grüneberg ganglion project to 10 specific glomeruli found in the caudal part of the olfactory bulb. Within a glomerulus, the axons originating from olfactory sensory neurons synapse on the dendrites of olfactory bulb neurons, including mitral and tufted cells. Mitral cells and tufted cells in turn project directly to higher brain centers (e.g., the piriform cortex and olfactory tubercle). The integration of olfactory information in the olfactory cortices and elsewhere in the central nervous system informs and directs animal behavior.

Open Source Tool For Network Monitoring

2010 ◽  
pp. 531-544
Author(s):  
Vreixo Formoso ◽  
Fidel Cacheda ◽  
Víctor Carneiro ◽  
Juan Valiño
Keyword(s):  
Open Source ◽  
Network Monitoring ◽  
Web Interface ◽  
Distributed Monitoring ◽  
Communications Networks ◽  
Remote Method Invocation ◽  
Real Environment ◽  
Extension System ◽  
Monitoring Tools ◽  
Configurable System

Even though monitoring tools are essential to the management of communications networks, Open Source applications still confront their potential users with considerable problems. This work analyses the limitations of the currently existing tools and presents the development of a new tool that solves most of those problems. The tool is based on a new architecture of objects and remote method invocation and allows both centralized and distributed monitoring. Its configuration through web interface, its support to monitoring templates, and its flexibility make it particularly interesting for a large number of users in search of a strong but easily configurable system. The proposed extension system is based on plug-ins and it is highly innovative because of its power and simplicity. Finally, the configuration simplicity and other essential improvements of the proposed system are successfully tested in a real environment.

scholarly journals Role of Axonal Odorant Receptors in Olfactory Topography

2020 ◽  
Vol 15 ◽  
pp. 263310552092341
Author(s):  
Claudia Lodovichi
Keyword(s):  
Olfactory Bulb ◽  
Sensory Neurons ◽  
Axon Terminal ◽  
Internal Representation ◽  
Dual Role ◽  
Odorant Receptors ◽  
Topographic Map ◽  
And Function ◽  
Guidance Molecule

A unique feature in the organization of the olfactory system is the dual role of the odorant receptors: they detect odors in the nasal epithelium and they play an instructive role in the convergence of olfactory sensory neuron axons in specific loci, ie, glomeruli, in the olfactory bulb. The dual role is corroborated by the expression of the odorant receptors in 2 specific locations of the olfactory sensory neurons: the cilia that protrude in the nostril, where the odorant receptors interact with odors, and the axon terminal, a suitable location for a potential axon guidance molecule. The mechanism of activation and function of the odorant receptors expressed at the axon terminal remained unknown for almost 20 years. A recent study identified the first putative ligand of the axonal odorant receptors, phosphatidylethanolamine-binding protein1, a molecule expressed in the olfactory bulb. The distinctive mechanisms of activation of the odorant receptors expressed at the opposite locations in sensory neurons, by odors, at the cilia, and by molecules expressed in the olfactory bulb, at the axon terminal, explain the dual role of the odorant receptors and link the specificity of odor perception with its internal representation, in the topographic map.

Odorant Receptors in the Formation of the Olfactory Bulb Circuitry

Physiology ◽  
2012 ◽  
Vol 27 (4) ◽  
pp. 200-212 ◽  
Author(s):  
Claudia Lodovichi ◽  
Leonardo Belluscio
Keyword(s):  
Olfactory Bulb ◽  
Axon Guidance ◽  
Sensory Neurons ◽  
Odorant Receptors ◽  
Olfactory Sensory Neurons ◽  
Neural Connectivity ◽  
Axon Terminals ◽  
Primary Function

In mammals, smell is mediated by odorant receptors expressed by sensory neurons in the nose. These specialized receptors are found both on olfactory sensory neurons' cilia and axon terminals. Although the primary function of ciliary odorant receptors is to detect odorants, their axonal role remains unclear but is thought to involve axon guidance. This review discusses findings that show axonal odorant receptors are indeed functional and capable of modulating neural connectivity.

The Holinshed Project: Comparing and linking two editions of Holinshed's Chronicle

2010 ◽  
Vol 4 (1-2) ◽  
pp. 39-53 ◽  
Author(s):  
James Cummings ◽  
Arno Mittelbach
Keyword(s):  
Open Source ◽  
Digital Humanities ◽  
Web Interface ◽  
Open Source Project ◽  
University Of Oxford ◽  
The University

This article documents the digital humanities aspects of The Holinshed Project at the University of Oxford. It outlines the nature of the project, in particular the need to compare paragraphs of the 1577 and 1587 editions of Holinshed's Chronicles of England, Scotland, and Ireland. In order to accomplish these comparisons, a tool known as the TEI-Comparator was created. This is a bespoke fuzzy text comparison engine with a frontend web interface designed for the project. The TEI-Comparator automatically matches reorganised and fragmented paragraphs in the two editions. It is then used for confirming, removing, creating and annotating the links between the editions. This article describes the steps necessary to use the TEI-Comparator, its comparison algorithm, and the handling of the output it creates with respect to its use for The Holinshed Project. The TEI-Comparator was launched in 2009 as an open source project on Sourceforge and is available for other projects to use.

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