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.