CIMAP AI Lab

👨‍🔬 About Dr. Aman Kaushik

Dr. Aman Kaushik – Bioinformatician at CIMAP

Dr. Aman Kaushik is a Scientist and Bioinformatician at Central Institute of Medicinal and Aromatic Plants (CIMAP), CSIR, India.

He specializes in integrating computational biology, cheminformatics, and artificial intelligence to drive innovations in plant genomics, natural products research, and molecular systems biology.

Currently, he is leading cutting-edge initiatives under the The Ayushman Bharat Digital Mission vision, targeting AI-powered agri-nutrition-biotech transformations for sustainable healthcare and agriculture.

🧠 Core Research Interests

🌿 CRISPR-Cas system discovery and annotation in environmental metagenomes
🧬 Transcriptomics & molecular biomarker discovery in human disease and plant systems
🔗 ceRNA regulatory networks in medicinal and aromatic plants
🤖 Artificial Intelligence for phytochemical drug discovery and metabolic pathway prediction
🧪 Comparative genomics of transporter gene families (e.g., sugar transporters) across plants and fungi

🧪 Our Team & AI Lab Environment

🧠 Areas of Expertise

AI-driven analysis of plant molecules

🌱 Core Research Areas

🌿 Plant Bioinformatics – Analysis of plant genomes, transcriptomes, and regulatory networks to uncover gene functions and pathways.
🧬 CRISPR & Genome Editing – Identification of CRISPR arrays and Cas proteins in metagenomes for targeted genome editing applications.
🤖 Computational Drug Design – In silico screening, molecular docking, and structure-based drug discovery from natural product libraries.
🧪 Phytochemical Profiling – Profiling and prediction of plant-derived bioactive compounds using cheminformatics and ML models.
📊 Machine Learning in Biology – Building predictive models for gene expression, protein function, and phytochemical classification.
🧫 Metagenomics & Microbiome Analysis – Taxonomic and functional analysis of microbial communities from environmental or plant rhizosphere samples.

📚 Integrating AI with Plant Sciences

AI lab interface for plant compounds

Intelligent discovery of plant metabolites

Plant genomics × AI × Metabolomics

💻 Developed Tools & Apps

Welcome to the portfolio of computational tools and pipelines developed to facilitate advanced bioinformatics analyses, particularly focusing on plant and microbial genomics, transcriptomics, and metabolomics.

These solutions are designed with dashboard-style interfaces, integrating AI models and domain-specific visualizations to help researchers intuitively explore and interpret complex biological data.

🛠️ Key Tools & Pipelines

🌿 PhytoChemX: Pipeline for phytochemical annotation and similarity screening, enabling researchers to identify and compare natural compounds efficiently.
🔗 ceRNET: Builds competing endogenous RNA (ceRNA) interaction networks to explore regulatory RNA interactions in plant systems.
🧬 CRISPR-Cas Detector: Metagenomic pipeline for predicting CRISPR arrays and Cas proteins, aiding microbial genome mining and functional annotation.
🧪 Satavarin Pathway Explorer: Tool for discovering genes involved in the biosynthesis of satavarin, advancing understanding of this valuable metabolite’s pathway.
🍬 SugarTransporter Hunter: Comparative genomics tool for analyzing sugar transporter genes across plant and fungal species.

These tools integrate advanced AI models and computational algorithms, illustrated by neural network architectures overlaid with plant metabolic pathways to highlight the synergy between machine learning and biological insight.

Our platforms aim to empower researchers with interactive, visually-rich environments to accelerate discoveries in plant science and bioinformatics.

📚 Selected Publications

Mehmood, A., Ali, M. S., Li, D., Kaushik, A., & Wei, D. Q. (2024). Unveiling the Therapeutic Potential of Paclitaxel Combinations Against Breast Carcinoma and Identification of In Vivo Biomarkers. Chemical Biology & Drug Design, 104(3), e14627.
Mehmood, A., Kaushik, A., & Wei, D. Q. (2024). DDSBC: A Stacking Ensemble Classifier-Based Approach for Breast Cancer Drug-Pair Cell Synergy Prediction. Journal of Chemical Information and Modeling, 64(16), 6421-6431.
Kaushik, A., & Zhao, Z. (2023). Machine learning-driven exploration of drug therapies for triple-negative breast cancer treatment. Frontiers in Molecular Biosciences, 10, 1215204.
Mehmood, A., Nawab, S., Jin, Y., Hassan, H., Kaushik, A., & Wei, D. Q. (2023). Ranking breast cancer drugs and biomarkers identification using machine learning and pharmacogenomics. ACS Pharmacology & Translational Science, 6(3), 399-409.
Kaushik, A., Wang, Y., Wang, X., & Wei, D. Q. (2021). Irinotecan and vandetanib create synergies for treatment of pancreatic cancer patients with concomitant TP53 and KRAS mutations. Briefings in Bioinformatics, 22(3).
Kaushik, A., Mehmood, A., Wei, D. Q., & Dai, X. (2020). Global ncRNAs expression profiling of TNBC and screening of functional lncRNA. Frontiers in Bioengineering and Biotechnology, 8, 1480.
Kaushik, A., Wu, Q., Lin, L., Li, H., Zhao, L., Wen, Z., Song, Y., Wu, Q., Wang, J., Guo, X., Wang, H., Yu, X., Wei, D. Q., & Zhang, S. (2021). Exosomal ncRNAs profiling of mycobacterial infection identified miRNA-185-5p as a novel biomarker for tuberculosis. Briefings in Bioinformatics. doi.org/10.1093/bib/bbab210.
Mehmood, A., Kaushik, A., Wang, Q., Li, C. D., & Wei, D. Q. (2021). Bringing Structural Implications and Deep Learning-Based Drug Identification for KRAS Mutants. Journal of Chemical Information and Modeling, 61(2), 571–586.
Kaushik, A., Mehmood, A., Dai, X., & Wei, D. Q. (2020). WeiBI (web-based platform): Enriching integrated interaction network with increased coverage and functional proteins from genome-wide experimental OMICS data. Scientific Reports, 10(1), 1-7.
Chu, Y., Kaushik, A., Wang, X., Wang, W., Zhang, Y., Shan, X., Salahub, D. R., Xiong, Y., & Wei, D. Q. (2019). DTI-CDF: a cascade deep forest model towards the prediction of drug-target interactions based on hybrid features. Briefings in Bioinformatics, 22(1), 451-462.

सीएसआईआर-केन्द्रीय औषधीय एवं सगंध पौधा संस्थान

CSIR-Central Institute of Medicinal and Aromatic Plants (CSIR-CIMAP)

🌿 CIMAP AI Lab