Faculty Opinions recommendation of agriGO: a GO analysis toolkit for the agricultural community.

2010 ◽  
Author(s):  
Daniel Chamovitz
Keyword(s):  
Go Analysis ◽  
Agricultural Community

scholarly journals agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update

2017 ◽  
Vol 45 (W1) ◽  
pp. W122-W129 ◽  
Author(s):  
Tian Tian ◽  
Yue Liu ◽  
Hengyu Yan ◽  
Qi You ◽  
Xin Yi ◽  
...  
Keyword(s):  
Go Analysis ◽  
Agricultural Community

scholarly journals agriGO: a GO analysis toolkit for the agricultural community

2010 ◽  
Vol 38 (suppl_2) ◽  
pp. W64-W70 ◽  
Author(s):  
Zhou Du ◽  
Xin Zhou ◽  
Yi Ling ◽  
Zhenhai Zhang ◽  
Zhen Su
Keyword(s):  
Go Analysis ◽  
Agricultural Community

Time Records in Mukkutar Pallu

2020 ◽  
Vol 1 (1) ◽  
pp. 1-21
Author(s):  
Kayalvizhy M
Keyword(s):  
Tamil Nadu ◽  
17Th Century ◽  
Social Conditions ◽  
Personal Life ◽  
Main Role ◽  
Agricultural Community

Mukkutar Pallu was an anonymous poem which depicts the life of Pallar community in the Southern part of Tamil Nadu during 17th century. They were ancient tribes and have a glorious past. The Pallers were the prominent agricultural community in the Tamil society. In this poem the poet records various events which were took place the 17th century. Pallar and Palliyar were the main role in this work. The poem beautifully records various events in the life of Pallar community. The personal life, agricultural works, religious conditions, belives, economic states, social conditions were beautifly recorded in this work. The feudal conduction at that time and the untouchablity a cruel custom which dominates the society at the time were recorded in this book. This book has considered as a time and historical valuable record of 17th century Tamil Nadu. The dialet which was spoke by the Pallar community were used in this book was this was the speciality of this book.

scholarly journals Precision agriculture and geospatial techniques for sustainable disease control

2021 ◽  
Author(s):  
Daniel P. Roberts ◽  
Nicholas M. Short ◽  
James Sill ◽  
Dilip K. Lakshman ◽  
Xiaojia Hu ◽  
...  
Keyword(s):  
Big Data ◽  
Disease Control ◽  
Crop Production ◽  
Plant Disease ◽  
Production Systems ◽  
Cropping Systems ◽  
Data Driven ◽  
Agricultural Community ◽  
Plant Disease Control ◽  
Crop Germplasm

AbstractThe agricultural community is confronted with dual challenges; increasing production of nutritionally dense food and decreasing the impacts of these crop production systems on the land, water, and climate. Control of plant pathogens will figure prominently in meeting these challenges as plant diseases cause significant yield and economic losses to crops responsible for feeding a large portion of the world population. New approaches and technologies to enhance sustainability of crop production systems and, importantly, plant disease control need to be developed and adopted. By leveraging advanced geoinformatic techniques, advances in computing and sensing infrastructure (e.g., cloud-based, big data-driven applications) will aid in the monitoring and management of pesticides and biologicals, such as cover crops and beneficial microbes, to reduce the impact of plant disease control and cropping systems on the environment. This includes geospatial tools being developed to aid the farmer in managing cropping system and disease management strategies that are more sustainable but increasingly complex. Geoinformatics and cloud-based, big data-driven applications are also being enlisted to speed up crop germplasm improvement; crop germplasm that has enhanced tolerance to pathogens and abiotic stress and is in tune with different cropping systems and environmental conditions is needed. Finally, advanced geoinformatic techniques and advances in computing infrastructure allow a more collaborative framework amongst scientists, policymakers, and the agricultural community to speed the development, transfer, and adoption of these sustainable technologies.

scholarly journals 975. Why Sex Make a Difference in HIV Clinical Course? Bioinformatics Analysis of Differential Expressed Gene in Females and Males with HIV Disease

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S516-S517
Author(s):  
Kulachanya Suwanwongse ◽  
Nehad Shabarek
Keyword(s):  
Gene Expression ◽  
Bioinformatics Analysis ◽  
Underlying Mechanism ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Gender Inequalities ◽  
Hiv Disease ◽  
Go Analysis ◽  
Hiv Progression ◽  
Pathway Analyses

Abstract Background Human immunodeficiency virus (HIV) disease progression are different among genders, in which women usually progress to acquired immunodeficiency syndrome (AIDS) faster than men. The mechanisms resulting in the gender biases of HIV progression are unclear. We conducted a bioinformatics analysis of differentially expressed genes (DEGs) in women and men with HIV disease to understand the sex-based differences in HIV pathogenesis. Methods We obtained microarray data from the Gene Expression Omnibus (GEO) database using our pre-defined search strategy and analyzed data using the GEO2R platform. The t-test was done to compare DEGs between females and males with HIV diseases. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was implemented to systematically extract biological features and processes of retrieving DEGs via gene ontology (GO) analysis. A Systemic search was performed to evaluate each DEG function and its possible association with HIV. Results One gene expression profiling data were retrieved: GSE 140713, composed of 40 males and 10 females with HIV1 infected samples. A GEO2R analysis yielded 19 DEGs (Table 1). The GO analysis result was demonstrated in Tables 2 and 3. Following a systemic search, we found two DEGs, which have previous studies reported an association with HIV: DDX3X (20 studies) and PDS5 (1 study). We proposed DDX3X (t 5.3, p 0.0037) is responsible for gender inequalities of HIV progression because of: 1. DDX3X is needed in the HIV1 life cycle. 2. Several studies confirmed a positive correlation between DDX3X expression and HIV1 replication. 3. Our study found an up-regulated DDX3X expression in women corresponded to the fact that women progress to AIDS faster than men. 4. Our GO analysis showed female up-regulated genes were enriched in positive regulation of the gene expression pathway, which can be explained by DDX3X and its underlying mechanism. Table 1: DEGs in women and men with HIV1 disease Table 2: GO functional enrichment pathway analyses of overall retrieving DEGs Table 3: GO functional enrichment pathway analyses of down- and up-regulated clusters of DEGs Conclusion Aberrant DDX3X expression may contribute to sex-based differences in HIV disease. Drugs modifying DDX3X gene expression will be beneficial in the treatment of HIV especially resolving the HIV drug resistance problem because current anti-HIV drugs target viral components posed the risk of viral mutation. Disclosures All Authors: No reported disclosures

scholarly journals A SYSTEM DESIGN OPTIMIZATION MODEL FOR INTEGRATED NATURAL RESOURCE CONSERVATION AND DEVELOPMENT IN AN AGRICULTURAL COMMUNITY

2021 ◽  
Vol 1 ◽  
pp. 273-282
Author(s):  
Thomas Barlow ◽  
Mandappa Biddanda ◽  
Samarth Mendke ◽  
Emmanuel Miyingo ◽  
Anabel Sicko ◽  
...  
Keyword(s):  
Natural Resource ◽  
Systems Approach ◽  
System Optimization ◽  
Resource Conservation ◽  
System Level ◽  
Conservation And Development ◽  
Natural Resource Conservation ◽  
Agricultural Community ◽  
System Design Optimization ◽  
System Configurations

AbstractIntegrated Natural Resource Conservation and Development (INRCD) Projects are efforts at worldwide locations to promote economic development of local communities consistent with conservation of natural resources. This umbrella term includes Integration Conservation and Development Projects (ICDPs) introduced by the World Wide Fund to combine social development and conservation s through the use of socio-economic investments, and the Integrated Natural Resource Management (INRM) research and development efforts that have employed a systems approach for quantitative modeling and optimization. In the spirit of the INRCD framework, we describe the development of a system-level agriculture and energy model comprising engineering and economic models for crop, irrigation, and energy subsystem designs for a community in Central Uganda. The model architecture is modular allowing modifications for different system configurations and project locations. We include some initial results and discuss next steps for system optimization, refining model assumptions, and modeling community social benefits as drivers of such projects.

RIM: Anatomy of a Weed Management Decision Support System for Adaptation and Wider Application

Weed Science ◽  
2015 ◽  
Vol 63 (3) ◽  
pp. 676-689 ◽  
Author(s):  
Myrtille Lacoste ◽  
Stephen Powles
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Weed Management ◽  
Cropping Systems ◽  
Integrated Management ◽  
Management Decision ◽  
Agricultural Community ◽  
End Use ◽  
Term Performance

RIM, or “Ryegrass Integrated Management,” is a model-based software allowing users to conveniently test and compare the long-term performance and profitability of numerous ryegrass control options used in Australian cropping systems. As a user-friendly decision support system that can be used by farmers, advisers, and industry professionals, RIM can aid the delivery of key recommendations among the agricultural community for broadacre cropping systems threatened by herbicide resistance. This paper provides advanced users and future developers with the keys to modify the latest version of RIM in order to facilitate future updates, modifications, and adaptations to other situations. The various components of RIM are mapped and explained, and the key principles underlying the construction of the model are explained. The implementation of RIM into a Microsoft Excel® software format is also documented, with details on how user inputs are coded and parameterized. An overview of the biological, agronomic, and economic components of the model is provided, with emphasis on the ryegrass biological characteristics most critical for its effective management. The extreme variability of these parameters and the subsequent limits of RIM are discussed. The necessary compromises were achieved by emphasizing the primary end-use of the program as a decision support system for farmers and advisors.

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