Biology subjects

Akter, N.

Publications and source records attributed to Akter, N..

3 recordsLinked to original sources

bioRxiv2026

GEO-BERT: A Retrieval augmented LLM Framework for Intelligent Dataset Retrieval from the Gene Expression Omnibus

The Gene Expression Omnibus (GEO) is a commonly used data repository of high throughput gene expression and other functional genomics data. This platform is globally used by researchers for submitting experimental datasets, accessing these datasets for hypothesis validation, reusing them in data-driven research, generating ideas for new research directions. Despite global usage, searching and identifying relevant and usable datasets in GEO remains challenging with an underlying keyword based search system needing manual intervention for the retrieval of desired datasets. GEO's inconsistent metadata and varying data annotation practices across submissions, variable data quality are contributing to its challenge for building structured query tools. With the recent advancement of Large Language Models (LLMs), it is timely to revisit the GEO datasets and its query system. Here, we present an AI chat-bot, GEO-BERT, leveraging an underlying retrieval augmented generator framework on the GEO metadata with a novel hierarchical hybrid field aware retrieval system to mine the datasets. GEO-BERT is locally installable, available for programmers and project developers (https://github.com/mrumi/GEOBERTtest) and readily usable by regular users on subset of test data. We demonstrated that GEO-BERT enhances the semantic search performance not currently available by any of the leading existing AI-powered chatbots, while improving the performance of GEO's traditional search performance for project development. Given the global usage of GEO and the latest advancement of the large language models, GEO-BERT fills the gap for context-aware extraction of GEO datasets.

bioinformatics↗

bioRxiv2021

Partial characterization and the evaluation of antimicrobial activities of silver nanoparticles biosynthesized from Cymbopogon citratus leaf extract

BackgroundSilver nanoparticles (AgNPs) are toxic to microorganisms and can potentially kill multidrug-resistant bacteria. Nanoparticles can be synthesized in many different ways, such as physical or chemical methods. Recently, it has been found that plant molecules can perform the same reduction reactions necessary for the production of nanoparticles but in a much more efficient way. ResultsHere, green chemistry was employed to synthesize silver nanoparticles using leaf extracts of Cymbopogon citratus. Effects of different parameters such as temperature, pH and volume of plant extract were also tested using their absorbance pattern at different wavelengths. The Surface Plasmon Resonance (SPR) changed with the changes in parameters. Changes in temperature from 20{degrees}C to 60{degrees}C have changed the highest absorbance from 0.972 to 3.893 with an SPR of 470 nm. At higher pH (11.1), the particles become highly unstable and have irregular shapes and sizes. At lower pH (3.97), the peak shifts to the right, indicating a smaller but unstable compound. We have also investigated the effect of the volume of plant extracts on the reaction time. The sample with the highest amount of plant extract showed the most absorbance with a value of 0.963 at {lambda}max, which was calculated to be 470 nm. The total formation of the AgNPs was observed visually with a color change from yellow to brownish-black. UV-visible spectroscopy was used to monitor the quantitative formation of silver nanoparticles, showing a signature peak in absorbance between 400 and 500 nm. We have estimated the size of the nanoparticles as 47nm by comparing the experimental data with the theoretical value using Mieplot. The biosynthesized silver nanoparticles showed enhanced antibacterial activity against several multidrug-resistant bacteria, determined based on the minimal inhibitory concentration and zone of inhibition. ConclusionThe findings of this study indicate that an aqueous extract of C. citratus can synthesize silver nanoparticles when silver nitrate is used as a precursor and silver nanoparticles act as antimicrobial properties enhancers. These findings can influence further studies in this field to better understand the properties and applications of nanoparticles.

molecular biology↗

bioRxiv2020

In silico chemical profiling and identification of neuromodulators from Curcuma amada targeting Acetylcholinesterase

Curcuma amada or Mango ginger, a member of the Zingiberaceae family, has been revealed as a beneficiary medicinal plant having diverse pharmacological activities against a wide range of diseases. Due to having neuromodulation properties of this plant, the present study characterized the secondary metabolites of Curcuma amada for their drug-likeness properties, identified potent hits by targeting Acetylcholinesterase (AChE) and revealed neuromodulatory potentiality by network pharmacology approaches. Here in silico ADMET analysis was performed for chemical profiling, and molecular docking and molecular dynamics simulations were used to hit selection and binding characterizations. Accordingly, ADMET prediction showed that around 87.59% of compounds processed drug-likeness activity, where four compounds have been screened out by molecular docking. Guided from induced-fit docking, molecular dynamics simulations revealed phytosterol and curcumin derivatives as the most favorable AChE inhibitors with the highest binding energy, as resulted from MM-PBSA analysis. Furthermore, all of the four hits were appeared to modulate several signaling molecules and intrinsic cellular pathways in network pharmacology analysis, which are associated with neuronal growth survival, inflammation, and immune response, supporting their capacity to revert the condition of neuro-pathobiology. Together, the present in silico based characterization and system pharmacology based findings demonstrate Curcuma amada, as a great source of neuromodulating compounds, which brings about new development for complementary and alternative medicine for the prevention and treatment of neurodegenerative disorders.

bioinformatics↗