Published in NAR Genomics and Bioinformatics, Volume 8, Issue 3, 2026
Conditional flow matching for cell-type-aware perturbation response prediction.
Recommended citation: Abir, Abrar Rahman, Sajib Acharjee Dip, and Liqing Zhang. (2026). "CFM-GP: Unified Conditional Flow Matching to Learn Gene Perturbation Across Cell Types." NAR Genomics and Bioinformatics 8(3): lqag087.
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Published in Journal of Experimental Botany, 2026
A community perspective on shared challenges, standards, and resources for comparative plant single-cell analysis.
Recommended citation: Haghani, Maryam, et al. (2026). "Cross-species plant single-cell analysis: community challenges and shared solutions." Journal of Experimental Botany, erag218.
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Published in Briefings in Bioinformatics, Volume 27, Issue 2, 2026
A cross-domain synthesis and taxonomy of agentic LLM systems in biology and biomedicine.
Recommended citation: Dip, Sajib Acharjee, et al. (2026). "Large Language Model Agents for Biological Intelligence Across Genomics, Proteomics, Spatial Biology, and Biomedicine." Briefings in Bioinformatics 27(2): bbag110.
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Published in Briefings in Bioinformatics, Volume 26, Issue 4, 2025
Unpaired cross-omics translation for robust multi-omics Alzheimer’s disease prediction.
Recommended citation: Abir, Abrar Rahman, Sajib Acharjee Dip, and Liqing Zhang. (2025). "UnCOT-AD: Unpaired Cross-Omics Translation Enables Multi-Omics Integration for Alzheimer's Disease Prediction." Briefings in Bioinformatics 26(4): bbaf438.
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Published in 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), Main Conference, 2026
A taxonomy and evaluation of foundation and agentic models for single-cell biology.
Recommended citation: Dip, Sajib Acharjee, et al. (2026). "LLM4Cell: Taxonomy and Evaluation of LLM and Agentic Models for Single-Cell Biology." Proceedings of ACL 2026, 41913-41954.
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Published in 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB 2026), 2026
Graph-based prediction of transcriptional responses for genes never perturbed during training.
Recommended citation: Dip, Sajib Acharjee, and Liqing Zhang. (2026). "Stable-Shift: Predicting Transcriptional Responses of Unseen Gene Perturbations Using Graph Neural Networks with Biological Priors." Proceedings of ACM BCB 2026, Article 101, 6 pages.
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Published in 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB 2026), 2026
Lightweight tissue-context fusion for frozen pathology foundation-model embeddings.
Recommended citation: Dip, Sajib Acharjee, and Liqing Zhang. (2026). "Patch-Level Tissue Context Improves Learning from Frozen Pathology Foundation Model Embeddings." Proceedings of ACM BCB 2026, Article 72, 6 pages.
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Published in Proceedings of the AAAI Symposium Series, Volume 4, Issue 1, 2024
Transfer learning and domain adaptation for skin-disease prediction across diverse skin tones.
Recommended citation: Dip, Sajib Acharjee, et al. (2024). "Equitable Skin Disease Prediction Using Transfer Learning and Domain Adaptation." Proceedings of the AAAI Symposium Series 4(1): 259-266.
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Published in 19th Machine Learning in Computational Biology Meeting (MLCB 2024), 2024
A genome foundation-model approach for pathogenicity detection from bacterial and viral DNA sequences.
Recommended citation: Dip, Sajib Acharjee. (2024). "PathoLM: Identifying Pathogenicity from the DNA Sequence Through the Genome Foundation Model." Proceedings of the 19th Machine Learning in Computational Biology Meeting, PMLR 261:153–161.
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