Overexpression of rice High-affinity Potassium Transporter gene OsHKT1;5 improves salinity and drought tolerance in Arabidopsis.

Background: Rice is subjected to various environmental stresses, resulting in significant production losses. Abiotic stresses, particularly drought and salinity, are the leading causes of plant damage worldwide. The High-affinity Potassium Transporter (HKT) gene family plays an important role in enhancing crop stress tolerance by regulating physiological and enzymatic functions.

A Hitchhiker's guide to RNA-RNA structure and interaction prediction tools.

RNA biology has risen to prominence after a remarkable discovery of diverse functions of noncoding RNA (ncRNA). Most untranslated transcripts often exert their regulatory functions into RNA-RNA complexes via base pairing with complementary sequences in other RNAs. An interplay between RNAs is essential, as it possesses various functional roles in human cells, including genetic translation, RNA splicing, editing, ribosomal RNA maturation, RNA degradation and the regulation of metabolic pathways/riboswitches.

Unraveling Roles of miR-27b-3p as a Potential Biomarker for Breast Cancer in Malay Women via Bioinformatics Analysis.

Abnormal miRNA expression has been associated with breast cancer. Knowing miRNA and its target genes gives a better understanding of the biological mechanism behind the development of breast cancer. Here, we evaluated the potential prognostic and predictive values of miRNAs in breast cancer development by analyzing Malay women with breast cancer expression profiles.

Chemoinformatics-driven classification of Angiosperms using sulfur-containing compounds and machine learning algorithm.

Background: Phytochemicals or secondary metabolites are low molecular weight organic compounds with little function in plant growth and development. Nevertheless, the metabolite diversity govern not only the phenetics of an organism but may also inform the evolutionary pattern and adaptation of green plants to the changing environment. Plant chemoinformatics analyzes the chemical system of natural products using computational tools and robust mathematical algorithms.

Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom.

In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized.

Genome-wide analysis of sulfur-encoding biosynthetic genes in rice (Oryza sativa L.) with Arabidopsis as the sulfur-dependent model plant.

Sulfur is an essential element required for plant growth and development, physiological processes and stress responses. Sulfur-encoding biosynthetic genes are involved in the primary sulfur assimilation pathway, regulating various mechanisms at the gene, cellular and system levels, and in the biosynthesis of sulfur-containing compounds (SCCs). In this study, the SCC-encoding biosynthetic genes in rice were identified using a sulfur-dependent model plant, the Arabidopsis.

A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms.

Soil salinity is one of the most serious environmental challenges, posing a growing threat to agriculture across the world. Soil salinity has a significant impact on rice growth, development, and production. Hence, improving rice varieties' resistance to salt stress is a viable solution for meeting global food demand.

Protein-Protein Interaction (PPI) Network of Zebrafish Oestrogen Receptors: A Bioinformatics Workflow.

Protein-protein interaction (PPI) is involved in every biological process that occurs within an organism. The understanding of PPI is essential for deciphering the cellular behaviours in a particular organism. The experimental data from PPI methods have been used in constructing the PPI network.

Comparative genome-wide analysis of WRKY, MADS-box and MYB transcription factor families in Arabidopsis and rice.

Transcription factors (TFs) form the major class of regulatory genes and play key roles in multiple plant stress responses. In most eukaryotic plants, transcription factor (TF) families (WRKY, MADS-box and MYB) activate unique cellular-level abiotic and biotic stress-responsive strategies, which are considered as key determinants for defense and developmental processes. Arabidopsis and rice are two important representative model systems for dicot and monocot plants, respectively.

A Comprehensive Gene Inventory for Glucosinolate Biosynthetic Pathway in .

Glucosinolates (GSLs) are plant secondary metabolites comprising sulfur and nitrogen mainly found in plants from the order of Brassicales, such as broccoli, cabbage, and . The activated forms of GSL play important roles in fighting against pathogens and have health benefits to humans. The increasing amount of data on generated from various omics technologies can be investigated more deeply in search of new genes or compounds involved in GSL biosynthesis and metabolism.

SuCComBase: a manually curated repository of plant sulfur-containing compounds.

Plants produce a wide range of secondary metabolites that play important roles in plant defense and immunity, their interaction with the environment and symbiotic associations. Sulfur-containing compounds (SCCs) are a group of important secondary metabolites produced in members of the Brassicales order. SCCs constitute various groups of phytochemicals, but not much is known about them.

Computational Analysis of Bioactive Compounds as Dipeptidyl Peptidase-IV Inhibitor.

The inhibition of dipeptidyl peptidase-IV (DPPIV) is a popular route for the treatment of type-2 diabetes. Commercially available gliptin-based drugs such as sitagliptin, anagliptin, linagliptin, saxagliptin, and alogliptin were specifically developed as DPPIV inhibitors for diabetic patients. The use of in treating diabetes had been reported in various in vitro experiments.