01
Crop biology
Read disease in the plant and design sampling around the biological question.
- Plant pathology
- Field sampling
- Infection assays
Crop biology, measured carefully
Prem Pratap Singh
Plant Scientist · Data Scientist · Molecular Diagnostics
I study crop disease from the field sample to the final model. My work brings molecular diagnostics, multi-omics, and reproducible data analysis together to find signals that can improve crop decisions.
UC DavisGrapevine virologyOpen to Research Scientist and Data Scientist roles
How I work
Crop improvement is the destination. Data is how I get there.
Step 01
Start in the field
Observe before measuring
Evidence carried forward
327 vines followed across two growing seasons
What it changes
Define the plant response and the trait worth improving.
Capabilities
Crop biology is my domain. Data science is how I investigate it.
I connect plant pathology and molecular measurement with computation, statistics, and reproducible research delivery.
02
Molecular diagnostics
Build quantitative assays that move from laboratory validation to field use.
- RT-qPCR
- Digital PCR
- Assay validation
03
Omics & analytical
Measure gene activity and chemistry across the same biological system.
- RNA-seq
- GC-MS
- LC-MS/MS
04
Data science
Turn complex measurements into reproducible models and interpretable evidence.
- Python & R
- Machine learning
- Statistical modeling
05
Research delivery
Make the work reusable, reviewable, and clear to collaborators and decision-makers.
- Reproducible pipelines
- SOPs
- Scientific writing
Field to molecule
Biology defines what to measure.
Data to evidence
Models connect the measurements.
Evidence to crop
Interpretation returns to the decision.
Open the full capability indexEight technical domains · 96 methods and research practices08 domains
Capability index
08 domainsSelected domain
Bioinformatics & Statistical Analysis
23
core methods
- 01Differential expression (DESeq2, limma-voom, edgeR)
- 02Repeated-measures voom
- 03Pathway enrichment (GSEA, GO, KEGG, MapMan)
- 04Co-expression networks (WGCNA, GENIE3, DGCA)
- 05Multi-omics integration (MOFA)
- 06Machine-learning classification
- 07Biomarker discovery
- 08LASSO / random forest / SVM / gradient boosting
- 09Stability selection
- 10Cross-validation
Experience
Where I have done the work
Roles spanning crop research, data science, and the evaluation of scientific AI.
Sep 2023–Present
Davis, CA, USA
University of California, Davis
Postdoctoral Scholar
I lead the field, laboratory, and computational work for a grapevine-virus program, from vineyard sampling and dPCR through RNA sequencing and biological interpretation.
- 300+ crop samples
- 1.3B+ sequencing reads
- Reusable analysis pipelines
Field + data
01
Sep 2025–Present
Remote
Handshake AI
MOVE Fellow, AI Trainer (part-time)
I evaluate scientific reasoning in biology for frontier AI systems and document the failure patterns that matter to accuracy and trust.
- Biology-domain evaluation
- Reference answers
- Reasoning failure analysis
Scientific AI
02
2017–2023
India
Banaras Hindu University
Ph.D. Research Scholar
I developed plant-based treatments for food-borne molds by combining formulation chemistry, wet-lab assays, transcriptomics, and computational modeling.
- 85% less mold growth
- Toxin eliminated
- 6 first-author papers
Mechanism
03
Published research
Evidence that has passed peer review.
Journal articles and book chapters spanning plant disease, diagnostics, multi-omics, and food safety.
60published works
Browse the publication archiveFilter by format and method
2026
Grapevine Red Blotch Disease: An Emerging Threat to Global Viticulture
In Preparation
Authors & methods
P. P. Singh, K. Reddy, A. M. Boghozian, A. Oberholster, M. R. Sudarshana
ReviewMulti-omics
2026
Temporal dynamics of Grapevine red blotch virus accumulation in grapevine leaves is influenced by fruit maturity stages
Authors & methods
P. P. Singh, K. Reddy, H. Scully, A. M. Boghozian, C. Medina-Plaza, A. Oberholster, M. R. Sudarshana
RT-qPCRDigital PCRField samplingStatistical modeling
2026
Rethinking Arsenal: Non-TAL Effectors Drive Xanthomonas Virulence in Brassica
Authors & methods
R. Singh, P. P. Singh
ReviewPlant-Pathogen Interactions
2026
Systematic investigation of aflatoxigenic Aspergillus flavus inhibition: Integrating essential oils-based formulation with mathematical modeling and transcriptomic analysis
Authors & methods
P. P. Singh, R. Singh, P. K. Verma, B. Prakash
TranscriptomicsMathematical modelingGC-MSMode-of-action assays
2025
Ceramide and C1P: a lipid love story of Brassica–Sclerotinia interaction
Authors & methods
R. Singh, P. P. Singh
ReviewPlant-Pathogen Interactions
2025
Microbial genome editing with CRISPR–Cas9: recent advances and emerging applications across sectors
Fermentation
Authors & methods
C. Dudeja, A. Mishra, A. Ali, P. P. Singh, A. K. Jaiswal
ReviewCRISPR-Cas9
2024
Assessment of Trachyspermum ammi essential oil against Aspergillus flavus, aflatoxin B1 contamination, and post-harvest quality of Sorghum bicolor
Authors & methods
P. P. Singh, A. K. Jaiswal, R. Singh, A. Kumar, V. Gupta, T. S. Raghuvanshi, A. Sharma, B. Prakash
GC-MSAntifungal ScreeningPostharvest Analysis
2024
Essential oils as green promising alternatives to chemical preservatives for agri-food products
Authors & methods
B. Prakash, P. P. Singh, V. Gupta, T. S. Raghuvanshi
Molecular DockingToxicity AssessmentReview
Selected work
Research projects
Field studies, diagnostic methods, and mechanism work across crop and food systems.
What we did
A multi-year study of 327 vine samples across two growing seasons and four ripening stages, funded by state and federal agriculture agencies, measuring how Grapevine Red Blotch Virus changes grape chemistry and the wine made from it.
What the data showed
Infected vines lost roughly 4 points of sugar in a cool season and 10 in a hot one, so heat makes the damage about 2.6 times worse. The study also showed the virus does not trip the vine's immune system; it stops the vine from mounting its normal heat-stress response.
Methods and capabilities
- Experimental design
- Large-scale data analysis
- Reproducible pipelines
- Scientific writing
- RNA sequencing
- Snakemake
- DESeq2
- GC-MS
- R
- Python
What we did
Built and validated laboratory tests that measure how much virus is present in a vine, then ran them across more than ten vineyard blocks to follow infection through the season.
What the data showed
Growers can identify infected vines before symptoms are visible and see how infection spreads across a block, which directly informs costly replanting decisions.
Methods and capabilities
- Diagnostic test development
- Method validation
- Field sampling
- Statistical analysis
- RT-qPCR
- Digital PCR
What we did
Designed a plant-oil treatment wrapped inside tiny food-safe particles that stops a mold responsible for contaminating stored grain and nuts with aflatoxin, a known human carcinogen.
What the data showed
Blocked over 90% of toxin production using food-safe, plant-derived ingredients, offering a practical alternative to synthetic chemical preservatives.
Methods and capabilities
- Formulation development
- Antimicrobial testing
- Materials characterization
- Food safety
- Nano-encapsulation
- Chitosan
- GC-MS
- Electron microscopy
Where the work can grow next
Better crop decisions, built on stronger biological data.
Research Scientist and Data Scientist roles
Ag-biotech · diagnostics · trait discovery
Research collaborations
Field biology · multi-omics · reproducible analysis
Scientific consulting
From experimental design to decision-ready evidence
Start a conversation
pr0982@gmail.com
Occasional field notes
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