scholarly journals Gexplora – user interface that highlights and explores the density of genomic elements along a chromosomal sequence

2020 ◽  
Author(s):  
Thomas Nussbaumer ◽  
Olivia Debnath ◽  
Parviz Heidari
Keyword(s):  
User Interface ◽  
Transposable Elements ◽  
Detailed Analysis ◽  
Candidate Genes ◽  
Graphical User Interface ◽  
Genomic Sequence ◽  
A Genome ◽  
Rest Api ◽  
Protein Datasets ◽  
Chromosomal Sequence

AbstractThe density of genomic elements such as genes or transposable elements along its consecutive sequence can provide an overview of a genomic sequence while in the detailed analysis of candidate genes it may depict enriched chromosomal hotspots harbouring genes that explain a certain trait. The herein presented python-based graphical user interface Gexplora allows to obtain more information about a genome by considering sequence-intrinsic information from external databases such as Ensembl, OMA and STRING database using REST API calls to retrieve sequence-intrinsic information, protein-protein datasets and orthologous groups. Gexplora is available under https://github.com/nthomasCUBE/Gexplora.

Application Research of Improved BP Algorithm

2011 ◽  
Vol 141 ◽  
pp. 88-91
Author(s):  
Cheng Yang ◽  
Chao Shi
Keyword(s):  
User Interface ◽  
Diagnostic Accuracy ◽  
Detailed Analysis ◽  
Graphical User Interface ◽  
Optimization Algorithm ◽  
Bp Algorithm ◽  
Application Research ◽  
Bp Network ◽  
Improved Bp Algorithm ◽  
Lm Algorithm

Based on JS engine, this paper made a detailed analysis on the standard BP algorithm, BP algorithm with additional momentum item, BP algorithm of parameter to adjust and BP network based on LM algorithm .Finally, this paper gets the optimization algorithm and network by comparing in training step and diagnostic accuracy. In the end, the front panel of the diagnosis system is designed by MATLAB graphical user interface.

HOW TO USE CROP GROWTH MODEL WOFOST FOR FORECASTING GROWTH AND YIELD OF A CROP

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
LAL SINGH ◽  
PARMEET SINGH ◽  
RAIHANA HABIB KANTH ◽  
PURUSHOTAM SINGH ◽  
SABIA AKHTER ◽  
...  
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Input Data ◽  
Growth And Yield ◽  
Weather Data ◽  
Data Sets ◽  
Crop Growth Model ◽  
Control Center ◽  
Field Crops ◽  
Crop Calendar

WOFOST version 7.1.3 is a computer model that simulates the growth and production of annual field crops. All the run options are operational through a graphical user interface named WOFOST Control Center version 1.8 (WCC). WCC facilitates selecting the production level, and input data sets on crop, soil, weather, crop calendar, hydrological field conditions, soil fertility parameters and the output options. The files with crop, soil and weather data are explained, as well as the run files and the output files. A general overview is given of the development and the applications of the model. Its underlying concepts are discussed briefly.

scholarly journals The Genetic Architecture of Ovariole Number in Drosophila melanogaster: Genes with Major, Quantitative, and Pleiotropic Effects

2017 ◽  
Vol 7 (7) ◽  
pp. 2391-2403 ◽  
Author(s):  
Amanda S Lobell ◽  
Rachel R Kaspari ◽  
Yazmin L Serrano Negron ◽  
Susan T Harbison
Keyword(s):  
Candidate Genes ◽  
Genome Wide Association Study ◽  
Natural Populations ◽  
Direct Role ◽  
Genome Wide ◽  
A Genome ◽  
Fitness Trait ◽  
Sleep Parameters ◽  
Activity Behavior ◽  
Ovariole Number

Abstract Ovariole number has a direct role in the number of eggs produced by an insect, suggesting that it is a key morphological fitness trait. Many studies have documented the variability of ovariole number and its relationship to other fitness and life-history traits in natural populations of Drosophila. However, the genes contributing to this variability are largely unknown. Here, we conducted a genome-wide association study of ovariole number in a natural population of flies. Using mutations and RNAi-mediated knockdown, we confirmed the effects of 24 candidate genes on ovariole number, including a novel gene, anneboleyn (formerly CG32000), that impacts both ovariole morphology and numbers of offspring produced. We also identified pleiotropic genes between ovariole number traits and sleep and activity behavior. While few polymorphisms overlapped between sleep parameters and ovariole number, 39 candidate genes were nevertheless in common. We verified the effects of seven genes on both ovariole number and sleep: bin3, blot, CG42389, kirre, slim, VAChT, and zfh1. Linkage disequilibrium among the polymorphisms in these common genes was low, suggesting that these polymorphisms may evolve independently.

scholarly journals Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 192
Author(s):  
Xinghai Duan ◽  
Bingxing An ◽  
Lili Du ◽  
Tianpeng Chang ◽  
Mang Liang ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Candidate Genes ◽  
Growth Curve ◽  
Growth And Development ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Coefficient Of Determination ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
A Genome

The objective of the present study was to perform a genome-wide association study (GWAS) for growth curve parameters using nonlinear models that fit original weight–age records. In this study, data from 808 Chinese Simmental beef cattle that were weighed at 0, 6, 12, and 18 months of age were used to fit the growth curve. The Gompertz model showed the highest coefficient of determination (R2 = 0.954). The parameters’ mature body weight (A), time-scale parameter (b), and maturity rate (K) were treated as phenotypes for single-trait GWAS and multi-trait GWAS. In total, 9, 49, and 7 significant SNPs associated with A, b, and K were identified by single-trait GWAS; 22 significant single nucleotide polymorphisms (SNPs) were identified by multi-trait GWAS. Among them, we observed several candidate genes, including PLIN3, KCNS3, TMCO1, PRKAG3, ANGPTL2, IGF-1, SHISA9, and STK3, which were previously reported to associate with growth and development. Further research for these candidate genes may be useful for exploring the full genetic architecture underlying growth and development traits in livestock.

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