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University of Illinois Urbana-Champaign

To view the full list of publications across IGB's research portfolio, please visit our Illinois Experts page. 

2024
 
Zilberman, D., Hochman, G., Khanna, M., & Wesseler, J. (2024). The political economy of the bioeconomy. In Handbook on the Bioeconomy (pp. 38-50). Edward Elgar Publishing. https://doi.org/10.4337/9781800373495.00010

 

 

Zhou, Y., Zhou, S., Lyons, S., Sun, H., Sweedler, J. V., & Lu, Y. (2024). Enhancing 2-Pyrone Synthase Efficiency by High-Throughput Mass-Spectrometric Quantification and In Vitro/In Vivo Catalytic Performance Correlation. ChemBioChem, 25(5), Article e202300849. https://doi.org/10.1002/cbic.202300849

 

 

Zhou, Q., Guan, K., Wang, S., Hipple, J., & Chen, Z. (2024). From satellite-based phenological metrics to crop planting dates: Deriving field-level planting dates for corn and soybean in the U.S. Midwest. ISPRS Journal of Photogrammetry and Remote Sensing, 216, 259-273. https://doi.org/10.1016/j.isprsjprs.2024.07.031

 

 

Zhong, X., Du, Y., Ouyang, S., Zhong, M., Luo, T., Ho, Q., Peng, H., Ji, H., & Han, J. (2024). ActionIE: Action Extraction from Scientific Literature with Programming Languages. In L.-W. Ku, A. F. T. Martins, & V. Srikumar (Eds.), Long Papers (pp. 12656-12671). (Proceedings of the Annual Meeting of the Association for Computational Linguistics; Vol. 1). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.acl-long.683

 

 

Zheng, R., Jia, Y., Ullagaddi, C., Allen, C., Rausch, K., Singh, V., Schnable, J. C., & Kamruzzaman, M. (2024). Optimizing feature selection with gradient boosting machines in PLS regression for predicting moisture and protein in multi-country corn kernels via NIR spectroscopy. Food chemistry, 456, Article 140062. https://doi.org/10.1016/j.foodchem.2024.140062

 

 

Zhao, S., Liu, X., Banerjee, S., Hartmann, M., Peng, B., Elvers, R., Zhao, Z. Y., Zhou, N., Liu, J. J., Wang, B., Tian, C. Y., Jiang, J., & Lian, T. X. (2024). Continuous planting of euhalophyte Suaeda salsa enhances microbial diversity and multifunctionality of saline soil. Applied and environmental microbiology, 90(4). https://doi.org/10.1128/aem.02355-23

 

 

Zhao, H. (2024). Synthetic Biology Continues to Grow. ACS synthetic biology, 13(1), 1-2. https://doi.org/10.1021/acssynbio.3c00765

 

 

Zhao, Y., Park, I., Rubakhin, S. S., Bashir, R., Vlasov, Y., & Sweedler, J. V. (2024). 1-Octanol-assisted ultra-small volume droplet microfluidics with nanoelectrospray ionization mass spectrometry. Analytica Chimica Acta, 1321, Article 342998. https://doi.org/10.1016/j.aca.2024.342998

 

 

Zhao, H., Cao, M., Tran, V., & Fatma, Z. (2024). Genetic toolbox for metabolic engineering of non-conventional yeast. (U.S. Patent No. 12116580).

 

 

Zhao, S., van der Heijden, M. G. A., Banerjee, S., Liu, J. J., Gu, H. D., Zhou, N., Yin, CH. H., Peng, B., Liu, X., Wang, B. Z., & Tian, C. Y. (2024). The role of halophyte-induced saline fertile islands in soil microbial biogeochemical cycling across arid ecosystems. Communications biology, 7(1), Article 1061. https://doi.org/10.1038/s42003-024-06741-1

 

 

Zhang, Z., Gomes Viana, J. P., Zhang, B., Walden, K. K. O., Müller Paul, H., Moose, S. P., Morris, G. P., Daum, C., Barry, K. W., Shakoor, N., & Hudson, M. (2024). Major impacts of widespread structural variation on sorghum. Genome Research, 34(2), 286-299. https://doi.org/10.1101/gr.278396.123

 

 

Zhang, Z., Reddy, R. G., Small, K., Zhang, T., & Ji, H. (2024). Towards Better Generalization in Open-Domain Question Answering by Mitigating Context Memorization. In K. Duh, H. Gomez, & S. Bethard (Eds.), Findings of the Association for Computational Linguistics: NAACL 2024 - Findings (pp. 742-753). (Findings of the Association for Computational Linguistics: NAACL 2024 - Findings). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.findings-naacl.48

 

 

Zhang, H., Diao, S., Lin, Y., Fung, Y. R., Lian, Q., Wang, X., Chen, Y., Ji, H., & Zhang, T. (2024). R-Tuning: Instructing Large Language Models to Say ‘I Don’t Know’. In K. Duh, H. Gomez, & S. Bethard (Eds.), Long Papers (pp. 7106-7132). (Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024; Vol. 1). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.naacl-long.394

 

 

Zhang, Z., Eddy, W. C., Stuchiner, E. R., DeLucia, E. H., & Yang, W. (2024). A conceptual model explaining spatial variation in soil nitrous oxide emissions in agricultural fields. Communications Earth and Environment, 5(1), Article 730. https://doi.org/10.1038/s43247-024-01875-w

 

 

Zhang, X., Arnold, W. A., Wright, N., Novak, P. J., & Guest, J. S. (2024). Prioritization of Early-Stage Research and Development of a Hydrogel-Encapsulated Anaerobic Technology for Distributed Treatment of High Strength Organic Wastewater. Environmental Science and Technology, 58(44), 19651-19665. https://doi.org/10.1021/acs.est.4c05389

 

 

Zhang, Z., & Ji, H. (2024). Enriching Conceptual Knowledge in Language Models through Metaphorical Reference Explanation. In M. Ogrodniczuk, A. Nedoluzhko, M. Poesio, S. Pradhan, & V. Ng (Eds.), Proceedings of the 7th Workshop on Computational Models of Reference, Anaphora and Coreference, CRAC 2024 (pp. 18-22). (Proceedings of the 7th Workshop on Computational Models of Reference, Anaphora and Coreference, CRAC 2024). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.crac-1.2

 

 

Zhai, A. J., Shen, Y., Chen, E. Y., Wang, G. X., Wang, X., Wang, S., Guan, K., & Wang, S. (2024). Physical Property Understanding from Language-Embedded Feature Fields. In Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024 (pp. 28296-28305). (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). IEEE Computer Society. https://doi.org/10.1109/CVPR52733.2024.02673

 

 

Yuan, L., Chen, Y., Wang, X., Fung, Y. R., Peng, H., & Ji, H. (2024). CRAFT: CUSTOMIZING LLMS BY CREATING AND RETRIEVING FROM SPECIALIZED TOOLSETS. Paper presented at 12th International Conference on Learning Representations, ICLR 2024, Hybrid, Vienna, Austria.

 

 

Yu, S., Gautam, A. K., Gao, D., Kuhn, A. N., He, H., Mironenko, A. V., & Yang, H. (2024). Implication of surface oxidation of nanoscale molybdenum carbide on electrocatalytic activity. Journal of Materials Chemistry A, 12(25), 15163-15176. https://doi.org/10.1039/D4TA01746C

 

 

Yu, C., Khanna, M., Atallah, S. S., Kar, S., Bagavathiannan, M., & Chowdhary, G. (2024). Herbicide-resistant weed management with robots: A weed ecological–economic model. Agricultural Economics (United Kingdom), 55(6), 943-962. https://doi.org/10.1111/agec.12856

 

 

Yu, P., & Ji, H. (2024). Information Association for Language Model Updating by Mitigating LM-Logical Discrepancy. In L. Barak, & M. Alikhani (Eds.), CoNLL 2024 - 28th Conference on Computational Natural Language Learning, Proceedings of the Conference (pp. 117-129). (CoNLL 2024 - 28th Conference on Computational Natural Language Learning, Proceedings of the Conference). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.conll-1.10

 

 

You, H., Hui, J., Zhou, Y., Vittore, K., Zhang, J., Chaney, L. E., Chinta, S., Zhao, Y., Lim, G., Lee, D. K., Ainsworth, E. A., Dunn, J. B., Dravid, V. P., Hersam, M. C., & Rowan, S. J. (2024). Sustainable Production of Biomass-Derived Graphite and Graphene Conductive Inks from Biochar. Small, 20(52), Article 2406669. https://doi.org/10.1002/smll.202406669

 

 

Yin, S., Mi, X., & Shukla, D. (2024). Leveraging machine learning models for peptide–protein interaction prediction. RSC Chemical Biology, 5(5), 401-417. https://doi.org/10.1039/D3CB00208J

 

 

Ye, F., Paulson, N., & Khanna, M. (2024). Strategic innovation and technology adoption under technological uncertainty. Journal of Economic Dynamics and Control, 165, Article 104879. https://doi.org/10.1016/j.jedc.2024.104879

 

 

Yang, Y., Peng, B., Guan, K., Pan, M., Franz, T. E., Cosh, M. H., & Bernacchi, C. J. (2024). Within-field soil moisture variability and time-invariant spatial structures of agricultural fields in the US Midwest. Vadose Zone Journal, 23(4), Article e20337. https://doi.org/10.1002/vzj2.20337

 

 

Yang, Y., Guan, K., Peng, B., Liu, Y., & Pan, M. (2024). Explicit Consideration of Plant Xylem Hydraulic Transport Improves the Simulation of Crop Response to Atmospheric Dryness in the U.S. Corn Belt. Water Resources Research, 60(6), Article e2023WR036468. https://doi.org/10.1029/2023WR036468

 

 

Yan, K., Li, X., Ling, H., Ashen, K., Edwards, C., Arróyave, R., Zitnik, M., Ji, H., Qian, X., Qian, X., & Ji, S. (2024). Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation. Advances in Neural Information Processing Systems, 37.

 

 

Xun, G., Zhu, Z., Singh, N., Lu, J., Jain, P. K., & Zhao, H. (2024). Harnessing noncanonical crRNA for highly efficient genome editing. Nature communications, 15(1), Article 3823. https://doi.org/10.1038/s41467-024-48012-x

 

 

Xu, C., Shaw, T., Choppararu, S. A., Lu, Y., Farooq, S. N., Qin, Y., Hudson, M., Weekley, B., Fisher, M., He, F., Da Silva Nascimento, J. R., Wergeles, N., Joshi, T., Bates, P. D., Koo, A. J., Allen, D. K., Cahoon, E. B., Thelen, J. J., & Xu, D. (2024). FatPlants: a comprehensive information system for lipid-related genes and metabolic pathways in plants. Database, 2024, Article baae074. https://doi.org/10.1093/database/baae074

 

 

Xiong, W., Dong, H., Ye, C., Wang, Z., Zhong, H., Ji, H., Jiang, N., & Zhang, T. (2024). Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint. Proceedings of Machine Learning Research, 235, 54715-54754.

 

 

Xin, K., Wang, Q., Chen, J., Yu, P., Zhao, H., & Ji, H. (2024). Gene-Metabolite Association Prediction with Interactive Knowledge Transfer Enhanced Graph for Metabolite Production. In M. Cannataro, H. Zheng, L. Gao, J. Cheng, J. L. de Miranda, E. Zumpano, X. Hu, Y.-R. Cho, & T. Park (Eds.), Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024 (pp. 383-388). (Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM62325.2024.10822779

 

 

Xie, Y. R., Castro, D. C., Rubakhin, S. S., Trinklein, T. J., Sweedler, J. V., & Lam, F. (2024). Multiscale biochemical mapping of the brain through deep-learning-enhanced high-throughput mass spectrometry. Nature Methods, 21(3), 521-530. https://doi.org/10.1038/s41592-024-02171-3

 

 

Xie, Z., Kim, C., Miller, M. J., & Jin, Y. S. (2024). Effects of 2′-fucosyllactose on the viability of starter cultures and Bifidobacterium strains of human origin in yogurt during refrigerated storage. Journal of food science, 89(5), 2546-2556. https://doi.org/10.1111/1750-3841.16996

 

 

Xie, Z., McAuliffe, O., Jin, Y. S., & Miller, M. J. (2024). Invited review: Genomic modifications of lactic acid bacteria and their applications in dairy fermentation. Journal of Dairy Science, 107(11), 8749-8764. https://doi.org/10.3168/jds.2024-24989

 

 

Wu, G., Guan, K., Ainsworth, E. A., Martin, D. G., Kimm, H., & Yang, X. (2024). Solar-induced chlorophyll fluorescence captures the effects of elevated ozone on canopy structure and acceleration of senescence in soybean. Journal of experimental botany, 75(1), 350-363. https://doi.org/10.1093/jxb/erad356

 

 

Wu, G., Guan, K., Kimm, H., Miao, G., Yang, X., & Jiang, C. (2024). Ground far-red sun-induced chlorophyll fluorescence and vegetation indices in the US Midwestern agroecosystems. Scientific Data, 11(1), Article 228. https://doi.org/10.1038/s41597-024-03004-w

 

 

Wu, S., Fung, M., Li, S., Wan, Y., Chang, K. W., & Ji, H. (2024). MACAROON: Training Vision-Language Models To Be Your Engaged Partners. In Y. Al-Onaizan, M. Bansal, & Y.-N. Chen (Eds.), EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024 (pp. 7715-7731). (EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.findings-emnlp.454

 

 

Wolf, A., Chang, E., Kantola, I. B., Blanc-Betes, E., Masters, M. D., Marklein, A., Moore, C. E., Bernacchi, C. J., & DeLucia, E. H. (2024). Validating assumptions in calculating carbon dioxide removal by enhanced rock weathering in Kantola et al., 2023. Global change biology, 30(1), Article e17031. https://doi.org/10.1111/gcb.17031

 

 

Widener, S., Njuguna, J. N., Clark, L. V., Anzoua, K. G., Bagmet, L., Chebukin, P., Dwiyanti, M. S., Dzyubenko, E., Dzyubenko, N., Ghimire, B. K., Jin, X., Jørgensen, U., Kjeldsen, J. B., Nagano, H., Peng, J., Petersen, K. K., Sabitov, A., Seong, E. S., Yamada, T., ... Lipka, A. E. (2024). Genotype by environment model predictive ability in Miscanthus. GCB Bioenergy, 16(1), Article e13113. https://doi.org/10.1111/gcbb.13113

 

 

Weigle, A. T., & Shukla, D. (2024). The Arabidopsis AtSWEET13 transporter discriminates sugars by selective facial and positional substrate recognition. Communications biology, 7(1), Article 764. https://doi.org/10.1038/s42003-024-06291-6

 

 

Wang, S., Edupulapati, B., Hagel, J. M., Kwok, J. J., Quebedeaux, J. C., Khasbaatar, A., Baek, J. M., Davies, D. W., Ella Elangovan, K., Wheeler, R. M., Leakey, A. D. B., Hill, C. W., Varnavas, K. A., & Diao, Y. (2024). Highly stretchable, robust, and resilient wearable electronics for remote, autonomous plant growth monitoring. Device, 2(4), Article 100322. https://doi.org/10.1016/j.device.2024.100322

 

 

Wang, Y., Saha, U., Rubakhin, S. S., Roy, E. J., Smith, A. M., Sweedler, J. V., & Lam, F. (2024). High-resolution 1H-MRSI at 9.4 T by integrating relaxation enhancement and subspace imaging. NMR in Biomedicine, 37(10), Article e5161. https://doi.org/10.1002/nbm.5161

 

 

Wang, Q., Zhang, Z., Li, H., Liu, X., Han, J., Zhao, H., & Ji, H. (2024). Chem-FINESE: Validating Fine-Grained Few-shot Entity Extraction through Text Reconstruction. In Y. Graham, M. Purver, & M. Purver (Eds.), EACL 2024 - 18th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2024 (pp. 1-16). (EACL 2024 - 18th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2024). Association for Computational Linguistics (ACL).

 

 

Wang, X., Peng, H., Jabbarvand, R., & Ji, H. (2024). LETI: Learning to Generate from Textual Interactions. In K. Duh, H. Gomez, & S. Bethard (Eds.), Findings of the Association for Computational Linguistics: NAACL 2024 - Findings (pp. 223-239). (Findings of the Association for Computational Linguistics: NAACL 2024 - Findings). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.findings-naacl.16

 

 

Wang, X., Wang, Z., Liu, J., Chen, Y., Yuan, L., Peng, H., & Ji, H. (2024). MINT: EVALUATING LLMS IN MULTI-TURN INTERACTION WITH TOOLS AND LANGUAGE FEEDBACK. Paper presented at 12th International Conference on Learning Representations, ICLR 2024, Hybrid, Vienna, Austria.

 

 

Wang, Z., Hou, L., Lu, T., Wu, Y., Li, Y., Yu, H., & Ji, H. (2024). ENABLING LANGUAGE MODELS TO IMPLICITLY LEARN SELF-IMPROVEMENT. Paper presented at 12th International Conference on Learning Representations, ICLR 2024, Hybrid, Vienna, Austria.

 

 

Wang, Q., Edwards, C., Ji, H., & Hope, T. (2024). Towards a Human-Computer Collaborative Scientific Paper Lifecycle: A Pilot Study and Hands-On Tutorial. In R. Klinger, & N. Okazaki (Eds.), 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Tutorial Summaries (pp. 56-67). (2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Tutorial Summaries). European Language Resources Association (ELRA).

 

 

Wang, S., Wang, Z., Hao, Q., Peng, B., Li, P., Qi, X., & Zhang, Q. (2024). Cropping with Vicia villosa and native grass improves soil's bacterial structure and ecological network in a jujube orchard. PeerJ, 12(6), Article e17458. https://doi.org/10.7717/peerj.17458

 

 

Wang, Z., Mao, S., Wu, W., Ge, T., Wei, F., & Ji, H. (2024). Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration. In K. Duh, H. Gomez, & S. Bethard (Eds.), Long Papers (pp. 257-279). (Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024; Vol. 1). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.naacl-long.15

 

 

Wang, X., Chen, Y., Yuan, L., Zhang, Y., Li, Y., Peng, H., & Ji, H. (2024). Executable Code Actions Elicit Better LLM Agents. Proceedings of Machine Learning Research, 235, 50208-50232.

 

 

Wang, Q., Downey, D., Ji, H., & Hope, T. (2024). SCIMON: Scientific Inspiration Machines Optimized for Novelty. In L.-W. Ku, A. F. T. Martins, & V. Srikumar (Eds.), Long Papers (pp. 279-299). (Proceedings of the Annual Meeting of the Association for Computational Linguistics; Vol. 1). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.acl-long.18

 

 

Wang, Y., Cheng, C., Li, S., Ren, Y., Shao, B., Liu, G., Heng, P. A., & Zheng, N. (2024). Neural P3M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs. Advances in Neural Information Processing Systems, 37.

 

 

Walukiewicz, H. E., Farris, Y., Burnet, M. C., Feid, S. C., You, Y., Kim, H., Bank, T., Christensen, D., Payne, S. H., Wolfe, A. J., Rao, C. V., & Nakayasu, E. S. (2024). Regulation of bacterial stringent response by an evolutionarily conserved ribosomal protein L11 methylation. mBio, 15(10), Article 01773. https://doi.org/10.1128/mbio.01773-24

 

 

Wall, S., Lemonnier, P., Milliken, A. L., Davey, P., & Lawson, T. (2024). Simultaneous and Independent Abaxial and Adaxial Gas Exchange Measurements. In Methods in Molecular Biology (pp. 63-76). (Methods in Molecular Biology; Vol. 2790). Humana Press Inc.. https://doi.org/10.1007/978-1-0716-3790-6_4

 

 

Walker, B. J., Driever, S. M., Kromdijk, J., Lawson, T., & Busch, F. A. (2024). Tools for Measuring Photosynthesis at Different Scales. In Methods in Molecular Biology (pp. 1-26). (Methods in Molecular Biology; Vol. 2790). Humana Press Inc.. https://doi.org/10.1007/978-1-0716-3790-6_1

 

 

von Haden, A. C., Eddy, W. C., Burnham, M. B., Brzostek, E. R., Yang, W. H., & DeLucia, E. H. (2024). Root exudation links root traits to soil functioning in agroecosystems. Plant and Soil, 500(1-2), 403-416. https://doi.org/10.1007/s11104-024-06491-3

 

 

Vijayakumar, S., Wang, Y., Lehretz, G., Taylor, S., Carmo-Silva, E., & Long, S. (2024). Kinetic modeling identifies targets for engineering improved photosynthetic efficiency in potato (Solanum tuberosum cv. Solara). Plant Journal, 117(2), 561-572. https://doi.org/10.1111/tpj.16512

 

 

Viana, J. P. G., Avalos, A., Zhang, Z., Nelson, R., & Hudson, M. E. (2024). Common signatures of selection reveal target loci for breeding across soybean populations. Plant Genome, 17(1), Article e20426. https://doi.org/10.1002/tpg2.20426

 

 

Vialet-Chabrand, S., Matsubara, S., & Lawson, T. (2024). Editorial: Dynamic photosynthesis under non-steady conditions. Frontiers in Plant Science, 15, Article 1489818. https://doi.org/10.3389/fpls.2024.1489818

 

 

Tran, V. G., Mishra, S., Bhagwat, S. S., Shafaei, S., Shen, Y., Allen, J. L., Crosly, B. A., Tan, S. I., Fatma, Z., Rabinowitz, J. D., Guest, J. S., Singh, V., & Zhao, H. (2024). Correction to: An end-to-end pipeline for succinic acid production at an industrially relevant scale using Issatchenkia orientalis (Nature Communications, (2023), 14, 1, (6152), 10.1038/s41467-023-41616-9). Nature communications, 15(1), Article 1161. https://doi.org/10.1038/s41467-024-45331-x

 

 

Torres-Rodriguez, M. D., Lee, S. G., Roy Choudhury, S., Paul, R., Selvam, B., Shukla, D., Jez, J. M., & Pandey, S. (2024). Structure-function analysis of plant G-protein regulatory mechanisms identifies key Gα-RGS protein interactions. Journal of Biological Chemistry, 300(5), Article 107252. https://doi.org/10.1016/j.jbc.2024.107252

 

 

Time, A., Gomez-Casanovas, N., Mwebaze, P., Apollon, W., Khanna, M., DeLucia, E. H., & Bernacchi, C. J. (2024). Conservation agrivoltaics for sustainable food-energy production. Plants People Planet, 6(3), 558-569. https://doi.org/10.1002/ppp3.10481

 

 

Tilhou, N. W., Lee, D. K., Ramstein, G. P., Poudel, H. P., Edme, S. J., & Casler, M. D. (2024). Empirical comparison of genomic selection to phenotypic selection for biomass yield of switchgrass. Agronomy Journal, 116(5), 2318-2327. https://doi.org/10.1002/agj2.21639

 

 

Tao, H., Sethuraman, T. V., Shlapentokh-Rothman, M., Gupta, T., Ji, H., & Hoiem, D. (2024). WebWISE: Unlocking Web Interface Control for LLMs via Sequential Exploration. In K. Duh, H. Gomez, & S. Bethard (Eds.), Findings of the Association for Computational Linguistics: NAACL 2024 - Findings (pp. 3693-3711). (Findings of the Association for Computational Linguistics: NAACL 2024 - Findings). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.findings-naacl.234

 

 

Tanigawa, K., Yuchen, Q., Katsuhama, N., Sakoda, K., Wakabayashi, Y., Tanaka, Y., Sage, R., Lawson, T., & Yamori, W. (2024). C4 monocots and C4 dicots exhibit rapid photosynthetic induction response in contrast to C3 plants. Physiologia Plantarum, 176(4), Article e14431. https://doi.org/10.1111/ppl.14431

 

 

Tang, X., Deng, C., Wang, H., Wang, H., Zhao, Y., Shi, W., Fung, M., Zhou, W., Cao, J., Ji, H., Cohan, A., & Gerstein, M. (2024). MIMIR: A Customizable Agent Tuning Platform for Enhanced Scientific Applications. In D. I. H. Farias, T. Hope, & M. Li (Eds.), EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Proceedings of System Demonstrations (pp. 486-496). (EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Proceedings of System Demonstrations). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.emnlp-demo.49

 

 

Tan, Y., De La Toba, E., Rubakhin, S. S., Labriola, L. T., Canfield, C., Pan, D., & Sweedler, J. V. (2024). NanoLC-timsTOF-Assisted Analysis of Glycated Albumin in Diabetes-Affected Plasma and Tears. Journal of the American Society for Mass Spectrometry, 35(1), 106-113. https://doi.org/10.1021/jasms.3c00331

 

 

Tan, S. I., Ng, I. S., & Zhao, H. (2024). Metabolic Engineering of Nonmodel Yeast Issatchenkia orientalis SD108 for 5-Aminolevulinic Acid Production. Biotechnology and bioengineering, 122(2), 415-423. Advance online publication. https://doi.org/10.1002/bit.28877

 

 

Tan, G. D., Chaudhuri, U., Varela, S., Ahuja, N., & Leakey, A. D. B. (2024). Machine learning-enabled computer vision for plant phenotyping: a primer on AI/ML and a case study on stomatal patterning. Journal of experimental botany, 75(21), 6683-6703. https://doi.org/10.1093/jxb/erae395

 

 

Subramanian, C., McNamara, K., Croslow, S. W., Tan, Y., Hess, D., Kiseljak-Vassiliades, K., Wierman, M. E., Sweedler, J. V., & Cohen, M. S. (in press). Novel repurposing of sulfasalazine for the treatment of adrenocortical carcinomas, probably through the SLC7A11/xCT-hsa-miR-92a-3p-OIP5-AS1 network pathway. Surgery (United States), 177, Article 108832. https://doi.org/10.1016/j.surg.2024.07.075

 

 

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