Bridging biology, biotechnology, and computation to develop sustainable solutions for agriculture and environmental challenges.

🎓 Graduate in Agriculture with research experience in plant pathology, plant breeding, microbiology, and biotechnology.

🔬 I work at the intersection of experimental biology and computational science, integrating bioinformatics, genomics, and machine learning to solve problems in agriculture and environmental sustainability.

🌱 My research interests include:

🌾 Crop Improvement & Plant Genetics

🧬 Integrative Omics (Genomics • Transcriptomics • Proteomics)

🦠 Plant–Pathogen Interactions & Disease Resistance

🧪 Biotechnology & Molecular Plant Breeding

🧫 Microbial Enzymes for Plastic Biodegradation

🧠 Machine Learning in Agriculture

📊 Bioinformatics & Computational Biology

🌍 Sustainable Agriculture & Environmental Biotechnology

• EMS/SA mutagenesis in rice (BRRI dhan28)
• Screening blast-resistant mutants against Pyricularia oryzae
• SSR marker analysis and genetic diversity studies
• Heritability estimation and BLUP-based breeding analysis
• Trait network and yield driver analysis

• Molecular characterization of fungal pathogens
• Effector biology and virulence factors
• Host defense response mechanisms
• ITS-based phylogenetic and haplotype analysis

• Microbial degradation of LDPE plastics
• Enzyme extraction and purification
• Nano–enzyme synergistic degradation systems
• Green synthesis of ZnO, CuO, CeO₂ nanoparticles

• Mycelium-based biomaterials
• Agricultural waste valorization
• Bio-based sustainable materials

I develop reproducible computational workflows for biological data analysis.

• RNA-Seq analysis pipelines
• Differential gene expression analysis
• Functional annotation & pathway enrichment
• Genome-wide gene family analysis
• Comparative genomics

• Molecular docking
• Molecular dynamics simulation
• Protein–ligand interaction analysis
• Structure visualization

• Trait correlation analysis
• Graphical Lasso trait networks
• Partial correlation networks
• Machine learning trait prediction

Libraries:

Pandas • NumPy • SciPy • Scikit-learn • Matplotlib • Seaborn • ggplot2

Other tools:

ClustalW • TBtools • InterProScan • KEGG • STRING

Computational breeding pipeline integrating:

• BLUP estimation
• Heritability analysis
• Trait correlation analysis
• Graphical Lasso networks
• Machine learning trait prediction

Comprehensive evolutionary analysis of:

• SPL transcription factor family
• NB-LRR resistance genes

Analyses include:

• phylogenetic reconstruction
• conserved motif identification
• gene structure analysis
• chromosomal distribution

Research on microbial degradation of plastic polymers using:

• fungal enzyme systems
• nanoparticle-enhanced degradation
• SEM and FTIR characterization

Goal: eco-friendly plastic degradation technologies

Population genetics of plant pathogens:

• Alternaria destruens
• Cochliobolus sativus

Methods:

• ITS sequencing
• haplotype network analysis
• phylogenetic reconstruction

My research integrates wet-lab experimentation with computational modeling.

Key directions:

🧬 Enzyme engineering for plastic degradation
🤖 Machine learning for biodegradation optimization
🧪 Nano–enzyme hybrid degradation systems
🌾 Genomics-assisted crop improvement

I aim to develop integrative biological solutions combining biotechnology, computational biology, and artificial intelligence to address global challenges in:

🌾 sustainable agriculture
♻️ environmental biotechnology
🧬 genomic science

⭐ Exploring biological systems through data, computation, and experimentation to build a sustainable future.