RiceNet v2: an improved network prioritization server for rice genes.

Nucleic Acids Res

Department of Biotechnology, College of Life Sciences and Biotechnology, Yonsei University, Seoul, Korea

Published: July 2015

Rice is the most important staple food crop and a model grass for studies of bioenergy crops. We previously published a genome-scale functional network server called RiceNet, constructed by integrating diverse genomics data and demonstrated the use of the network in genetic dissection of rice biotic stress responses and its usefulness for other grass species. Since the initial construction of the network, there has been a significant increase in the amount of publicly available rice genomics data. Here, we present an updated network prioritization server for Oryza sativa ssp. japonica, RiceNet v2 (http://www.inetbio.org/ricenet), which provides a network of 25 765 genes (70.1% of the coding genome) and 1 775 000 co-functional links. Ricenet v2 also provides two complementary methods for network prioritization based on: (i) network direct neighborhood and (ii) context-associated hubs. RiceNet v2 can use genes of the related subspecies O. sativa ssp. indica and the reference plant Arabidopsis for versatility in generating hypotheses. We demonstrate that RiceNet v2 effectively identifies candidate genes involved in rice root/shoot development and defense responses, demonstrating its usefulness for the grass research community.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489288PMC
http://dx.doi.org/10.1093/nar/gkv253DOI Listing

Publication Analysis

Top Keywords

network prioritization
12
network
8
prioritization server
8
genomics data
8
sativa ssp
8
ricenet
6
rice
5
ricenet improved
4
improved network
4
server rice
4

Similar Publications

Objectives: Neurocritically ill patients are at high risk for developing delirium, which can worsen the long-term outcomes of this vulnerable population. However, existing delirium assessment tools do not account for neurologic deficits that often interfere with conventional testing and are therefore unreliable in neurocritically ill patients. We aimed to determine the accuracy and predictive validity of the Fluctuating Mental Status Evaluation (FMSE), a novel delirium screening tool developed specifically for neurocritically ill patients.

View Article and Find Full Text PDF

GraphkmerDTA: integrating local sequence patterns and topological information for drug-target binding affinity prediction and applications in multi-target anti-Alzheimer's drug discovery.

Mol Divers

January 2025

Key Laboratory of Prevention and Treatment of Cardiovascular and Cerebrovascular Diseases Ministry of Education, Jiangxi Province Key Laboratory of Biomaterials and Biofabrication for Tissue Engineering, Gannan Medical University, Ganzhou, 341000, Jiangxi, China.

Identifying drug-target binding affinity (DTA) plays a critical role in early-stage drug discovery. Despite the availability of various existing methods, there are still two limitations. Firstly, sequence-based methods often extract features from fixed length protein sequences, requiring truncation or padding, which can result in information loss or the introduction of unwanted noise.

View Article and Find Full Text PDF

Anthropogenically induced climate change has significantly increased the frequency of acute weather events, such as drought. As human activities amplify environmental stresses, animals may be forced to prioritize survival over behaviors less crucial to immediate fitness, such as socializing. Yet, social bonds may also enable individuals to weather the deleterious effects of environmental conditions.

View Article and Find Full Text PDF

As funding for large translational research consortia increases across the National Institutes of Health (NIH), focused working groups provide an opportunity to leverage the power of unique networks to conduct high-impact science and offer a strategy for building collaborative infrastructure to sustain networks long-term. This sustainment leverages the existing NIH investments, amplifying the impact and creating conditions for future innovative translational research. However, few resources exist that detail practical strategies for establishing and sustaining working groups in consortia.

View Article and Find Full Text PDF

Background: Cardiovascular diseases (CVDs) continue to be the world's greatest cause of death. To evaluate heart function and diagnose coronary artery disease (CAD), myocardial perfusion imaging (MPI) has become essential. Artificial intelligence (AI) methods have been incorporated into diagnostic methods such as MPI to improve patient outcomes in recent years.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!