Publications

Our publications demonstrate our philosophy of integrating chemical, biological, and clinical data to solve complex problems. Below are selected works grouped by our core research themes.

2026

1. Mittal A, Gupta M, Mohanty SK, Gaur A, Solanki S, Ali SY, Raza A, Sharma P, Kumar S, Gautam V, Satija S, Katyayan N, Tiwari K, Sharma AK, Kaur D, Sengupta D, Gupta SK, Ahuja G. Evolutionary-guided advanced deep-learning architecture powers mammalian GPCRome agonist predictions. Cell Rep. 2026 Feb 18;45(3):117003. doi: 10.1016/j.celrep.2026.117003. Epub ahead of print. PMID: 41719122.

2025

1. Bhattacharya N, Chakraborti S, Kumari S, Mathew B, Halder A, Gujral S, Gupta K, Mittal A, Sinha D, Nelson C, Chakraborty T, Ahuja G#, Sengupta D#. Network-based simultaneous embedding of cells and marker genes from scRNA-seq studies. Brief Bioinform. 2025;26(5):bbaf537. doi:10.1093/bib/bbaf537. (# Co-corresponding author)
   
   

2. Duari S, Gautam V, Ahuja G. Protocol for cellular age prediction in yeast and human single cells using transfer learning. STAR Protoc. 2025;6(3):104023. doi:10.1016/j.xpro.2025.104023.
   
   

3. Mohanty SK, Mittal A, Namra, Gaur A, Duari S, Solanki S, Sharma AK, Arora S, Kumar S, Gautam V, Dixit NK, Subramanian K, Ghosh TS, Sengupta D, Gupta SK, Murugan NA, Sharma D, Ahuja G. Deep learning reveals endogenous sterols as allosteric modulators of the GPCR–Gα interface. eLife. 2025;14:RP106397. doi:10.7554/eLife.106397.1.
   
   

4. Gautam V, Duari S, Solanki S, Gupta M, Mittal A, Arora S, Aggarwal A, Sharma AK, Tyagi S, Pankajbhai RK, Sharma A, Chauhan S, Satija S, Kumar S, Mohanty SK, Tayal J, Dixit NK, Sengupta D, Mehta A, Ahuja G. scCamAge: A context-aware prediction engine for cellular age, aging-associated bioactivities, and morphometrics. Cell Rep. 2025;44(2):115270. doi:10.1016/j.celrep.2025.115270.
   
   

5. Arora S, Mittal A, Duari S, Chauhan S, Dixit NK, Mohanty SK, Sharma A, Solanki S, Sharma AK, Gautam V, Gahlot PS, Satija S, Nanshi J, Kapoor N, Cb L, Sengupta D, Mehrotra P, Ghosh TS, Ahuja G. Discovering geroprotectors through the explainable artificial intelligence-based platform AgeXtend. Nat Aging. 2025;5(1):144–161. doi:10.1038/s43587-024-00763-4.
   
   

2024

1. Bhattacharya N, Rockstroh A, Deshpande SS, Thomas SK, Yadav A, Goswami C, Chawla S, Solomon P, Fourgeux C, Ahuja G, Hollier BG, Kumar H, Roquilly A, Poschmann J, Lehman M, Nelson CC, Sengupta D. Pseudo-grading of tumor subpopulations from single-cell transcriptomic data using phenotype algebra. eLife. 2024;13:RP98469. doi:10.7554/eLife.98469.1.
   
   

2. Rai P, Jain A, Kumar S, Sharma D, Jha N, Chawla S, Raj A, Gupta A, Poonia S, Majumdar A, Chakraborty T, Ahuja G#, Sengupta D#. Literature mining discerns latent disease–gene relationships. Bioinformatics. 2024;40(4):btae185. doi:10.1093/bioinformatics/btae185. (# Co-corresponding author)
   
   

3. Arora S, Satija S, Mittal A, Solanki S, Mohanty SK, Srivastava V, Sengupta D, Rout D, Arul Murugan N, Borkar RM, Ahuja G. Unlocking the mysteries of DNA adducts with artificial intelligence. ChemBioChem. 2024;25(1):e202300577. doi:10.1002/cbic.202300577.
   
   

2023

1. Mittal A, Ahuja G. Advancing chemical carcinogenicity prediction modeling: opportunities and challenges. Trends Pharmacol Sci. 2023;44:400–410.
   
   

2. Poonia S, Goel A, Chawla S, Bhattacharya N, Rai P, Lee YF, Yap YS, West J, Bhagat AA, Tayal J, Mehta A, Ahuja G, Majumdar A, Ramalingam N, Sengupta D. Marker-free characterization of full-length transcriptomes of single live circulating tumor cells. Genome Res. 2023;33:80–95.
   
   

3. Bartsch D, Kalamkar K, Ahuja G, Lackmann JW, Hescheler J, Weber T, Bazzi H, Clamer M, Mendjan S, Papantonis A, Kurian L. mRNA translational specialization by RBPMS presets the competence for cardiac commitment in hESCs. Sci Adv. 2023;9:eade1792.
   
   

4. Mohanty SK, Maryam S, Gautam V, Mittal A, Gupta K, Arora R, Bhadra W, Mishra T, Sengupta D, Ahuja G. Transcriptional advantage influences odorant receptor gene choice. Brief Funct Genomics. 2023;22(3):281–290. doi:10.1093/bfgp/elac052.
   
   

5. Saproo S, Sarkar SS, Gupta E, Chattopadhyay S, Charaya A, Kalra S, Ahuja G, Naidu S. MiR-330-5p and miR-1270 target essential components of RNA polymerase I transcription and exhibit a novel tumor suppressor role in lung adenocarcinoma. Cancer Gene Ther. 2023;30(2):288–301. doi:10.1038/s41417-022-00544-4.
   
   

2022

1. Saproo S, Sarkar SS, Gautam V, Konyak CW, Dass G, Karmakar A, Sharma M, Ahuja G, Gupta A, Tayal J, Mehta A, Naidu S. Salivary protein kinase C alpha and novel microRNAs as diagnostic and therapeutic resistance markers for oral squamous cell carcinoma in Indian cohorts. Front Mol Biosci. 2022;9:1106963.
   
   

2. Chawla S, Rockstroh A, Lehman M, Ratther E, Jain A, Anand A, Gupta A, Bhattacharya N, Poonia S, Rai P, Das N, Majumdar A, Jayadeva, Ahuja G, Hollier BG, Nelson CC, Sengupta D. Gene expression-based inference of cancer drug sensitivity. Nat Commun. 2022;13:5680. doi:10.1038/s41467-022-33291-z.
   
   

3. Mittal A, Mohanty SK, Gautam V, Arora S, Saproo S, Gupta R, Sivakumar R, Garg P, Aggarwal A, Raghavachary P, Dixit NK, Singh VP, Mehta A, Tayal J, Naidu S, Sengupta D, Ahuja G. Artificial intelligence uncovers carcinogenic human metabolites. Nat Chem Biol. 2022;18(11):1204–1213. doi:10.1038/s41589-022-01110-7.
   
   

4. Gautam V, Gupta R, Gupta D, Ruhela A, Mittal A, Mohanty SK, Arora S, Gupta R, Saini C, Sengupta D, Murugan NA, Ahuja G. deepGraphh: AI-driven web service for graph-based quantitative structure–activity relationship analysis. Brief Bioinform. 2022;23(5):bbac288. doi:10.1093/bib/bbac288.
   
   

5. Gupta P, Jindal A, Ahuja G, Jayadeva, Sengupta D. A new deep learning technique reveals the exclusive functional contributions of individual cancer mutations. J Biol Chem. 2022;298(8):102177. doi:10.1016/j.jbc.2022.102177.
   
   

6. Ruhela V, Gupta A, Sriram K, Ahuja G, Kaur G, Gupta R. A unified computational framework for robust identification of novel miRNAs from RNA sequencing data. Front Bioinform. 2022;2:842051.
   
   

2021

1. Gupta K, Yadav P, Maryam S, Ahuja G#, Sengupta D#. Quantification of age-related decline in transcriptional homeostasis. J Mol Biol. 2021;433(19):167179. doi:10.1016/j.jmb.2021.167179. (# Co-corresponding author)
   
   

2. Gupta R, Mittal A, Agrawal V, Gupta S, Gupta K, Jain RR, Garg P, Mohanty SK, Sogani R, Chhabra HS, Gautam V, Mishra T, Sengupta D, Ahuja G. OdoriFy: A conglomerate of artificial intelligence-driven prediction engines for olfactory decoding. J Biol Chem. 2021;297(2):100956. doi:10.1016/j.jbc.2021.100956.
   
   

3. Gautam V, Mittal A, Kalra S, Mohanty SK, Gupta K, Rani K, Naidu S, Mishra T, Sengupta D, Ahuja G. EcTracker: Tracking and elucidating ectopic expression leveraging large-scale scRNA-seq studies. Brief Bioinform. 2021;22:bbab237. doi:10.1093/bib/bbab237.
   
   

4. Bhattacharya N, Nelson CC, Ahuja G#, Sengupta D#. Big data analytics in single-cell transcriptomics: five grand opportunities. Wiley Interdiscip Rev Data Min Knowl Discov. 2021;11:e1414. doi:10.1002/widm.1414. (# Co-corresponding author)
   
   

5. Gupta K, Lalit M, Biswas A, Sanada CD, Greene C, Hukari K, Maulik U, Bandyopadhyay S, Ramalingam N, Ahuja G, Ghosh A, Sengupta D. Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-seq data. Genome Res. 2021;31:689–697.
   
   

6. Gupta A, Choudhary M, Mohanty SK, Mittal A, Gupta K, Arya A, Kumar S, Katyayan N, Dixit NK, Kalra S, Goel M, Sahni M, Singhal V, Mishra T, Sengupta D, Ahuja G. Machine-Olf-Action: A unified framework for developing and interpreting machine-learning models for chemosensory research. Bioinformatics. 2021;37(12):1769–1771. doi:10.1093/bioinformatics/btaa1104.
   
   

7. Gerkin RC, Ohla K, et al., Ahuja G, Parma V, GCCR Group. Recent smell loss is the best predictor of COVID-19 among individuals with recent respiratory symptoms. Chem Senses. 2021;46:bjaa081. doi:10.1093/chemse/bjaa081.
   
   

8. Kalra S, Mittal A, Bajoria M, Mishra T, Maryam S, Sengupta D, Ahuja G. Challenges and possible solutions for decoding extranasal olfactory receptors. FEBS J. 2021;288(14):4230–4241. doi:10.1111/febs.15606.
   
   

9. Gupta K, Mohanty SK, Mittal A, Kalra S, Kumar S, Mishra T, Ahuja J, Sengupta D, Ahuja G. The cellular basis of loss of smell in 2019-nCoV-infected individuals. Brief Bioinform. 2021;22(2):873–881. doi:10.1093/bib/bbaa168.
   
   

2020

1. Goswami C, Chawla S, Thakral D, Pant H, Verma P, Malik PS, Jayadeva, Gupta R, Ahuja G#, Sengupta D#. Molecular signature comprising 11 platelet genes enables accurate blood-based diagnosis of NSCLC. BMC Genomics. 2020;21:744. (# Co-corresponding author)
   
   

2. Kalra S, Mittal A, Gupta K, Singhal V, Gupta A, Mishra T, Naidu S, Sengupta D, Ahuja G. Analysis of single-cell transcriptomes links enrichment of olfactory receptors with cancer cell differentiation status and prognosis. Commun Biol. 2020;3:506. doi:10.1038/s42003-020-01232-5.
   
   

2019

1. Ahuja G, Bartsch D, Yao W, Geissen S, Frank S, Aguirre A, Russ N, Messling JE, Dodzian J, Lagerborg KA, Vargas NE, Muck JS, Brodesser S, Baldus S, Sachinidis A, Hescheler J, Dieterich C, Trifunovic A, Papantonis A, Petrascheck M, Klinke A, Jain M, Valenzano DR, Kurian L. Loss of genomic integrity induced by lysosphingolipid imbalance drives ageing in the heart. EMBO Rep. 2019;20:eXXXX.
   
   

2. Kuo CC, Hänzelmann S, Sentürk Cetin N, Frank S, Zajzon B, Derks JP, Akhade VS, Ahuja G, Kanduri C, Grummt I, Kurian L, Costa IG. Detection of RNA–DNA binding sites in long noncoding RNAs. Nucleic Acids Res. 2019;47:e32.
   
   

3. Frank S*, Ahuja G*, Bartsch D, Russ N, Yao W, Kuo JCC, Derks JP, Akhade VS, Kargapolova Y, Georgomanolis T, Messling JE, Gramm M, Brant L, Rehimi R, Vargas NE, Kuroczik A, Yang TP, Sahito RGA, Franzen J, Hescheler J, Sachinidis A, Peifer M, Rada-Iglesias A, Kanduri M, Costa IG, Kanduri C, Papantonis A, Kurian L. yylncT defines a class of divergently transcribed lncRNAs and safeguards T-mediated mesodermal commitment of human PSCs. Cell Stem Cell. 2019;24:318–327.e8. (* Co-first author)
   
   

2018

1. Ahuja G#, Reichel V, Kowatschew D, Syed AS, Kotagiri AK, Oka Y, Weth F, Korsching SI. Overlapping but distinct topology for zebrafish V2R-like olfactory receptors reminiscent of odorant receptor spatial expression zones. BMC Genomics. 2018;19:383. (# Corresponding author)
   
   

2017

1. Ju Lee H, Bartsch D, Xiao C, Guerrero S, Ahuja G, Schindler C, Moresco JJ, Yates JR III, Gebauer F, Bazzi H, Dieterich C, Kurian L, Vilchez D. A post-transcriptional program coordinated by CSDE1 prevents intrinsic neural differentiation of human embryonic stem cells. Nat Commun. 2017;8:1456.
   
   

2. Dieris M, Ahuja G, Krishna V, Korsching SI. A single identified glomerulus in the zebrafish olfactory bulb carries the high-affinity response to death-associated odor cadaverine. Sci Rep. 2017;7:40892.
   
   

2016

1. Sharma K, Ahuja G, Hussain A, Balfanz S, Baumann A, Korsching SI. Elimination of a ligand gating site generates a supersensitive olfactory receptor. Sci Rep. 2016;6:28359.
   
   

2015

1. Saraiva LR*, Ahuja G*, Ivandic I, Syed AS, Marioni JC, Korsching SI, Logan DW. Molecular and neuronal homology between the olfactory systems of zebrafish and mouse. Sci Rep. 2015;5:11487. (* Co-first author)
   
   

2014

1. Ahuja G, Bozorg Nia S, Zapilko V, Shiriagin V, Kowatschew D, Oka Y, Korsching SI. Kappe neurons, a novel population of olfactory sensory neurons. Sci Rep. 2014;4:4037.
   
   

2. Ahuja G, Korsching S. Zebrafish olfactory receptor ORA1 recognizes a putative reproductive pheromone. Commun Integr Biol. 2014;7:eXXXX.
   
   

3. Behrens M, Frank O, Rawel H, Ahuja G, Potting C, Hofmann T, Meyerhof W, Korsching S. ORA1, a zebrafish olfactory receptor ancestral to all mammalian V1R genes, recognizes 4-hydroxyphenylacetic acid, a putative reproductive pheromone. J Biol Chem. 2014;289:19778–19788.
   
   

2013

1. Hussain A*, Saraiva LR*, Ferrero DM*, Ahuja G*, Krishna VS, Liberles SD, Korsching SI. High-affinity olfactory receptor for the death-associated odor cadaverine. Proc Natl Acad Sci USA. 2013;110:19579–19584. (* Co-first author)

2. Ahuja G, Ivandic I, Saltürk M, Oka Y, Nadler W, Korsching SI. Zebrafish crypt neurons project to a single, identified mediodorsal glomerulus. Sci Rep. 2013;3:2063.