Publications

Precision medicine

11. Choi, G.; Cheon, J.; Yoo, C.; Courcoubetis, G.; Ryoo, B.-Y.; Kim, K.-P.; Chang, H.-M.; Oh, H.-S.; Lim, S.; Koo, J.*; Kim, M.*. Predicting chemotherapy response in patients with advanced or metastatic pancreatic cancer using machine learning. In review.

10. Tsang, J.; Yap, Q.J.; Kapoor, S.; Cromarty, J.; Sen, S.; Kim, M.; Courcoubetis, G.; Cho, S.; Swartzfager, D.; Park, S.; Lim, S.; Holcomb, I.*; Koo, J.*. Identification of novel genetic mutations for the treatment prognostication of canine lymphoma. In review.

9. Choi, G.; Yap, Q.J.; Ko, N.; Namgoong, S.; Lee, H.; Oh, M.; Choi, G.; Lim, S.; Koo, J.*. A study on the relationship between MDR1 mutation and ex vivo drug sensitivities of canine lymphomas. Accepted for publication @ Biotechnology and Bioprocess Engineering.

8. Lee, H.; Ko, N.; Namgoong, S.; Ham, S.; Koo, J.*. Recent advances in and applications of ex vivo drug sensitivity analysis for blood cancers. Blood Research 2024, 59, 37.

7. Kapoor, S.; Sen, S.; Tsang, J.; Yap, Q.J.; Park, S.; Cromarty, J.; Swartzfager, D.; Choy, K.; Lim, S., Koo, J.*; Holcomb, I.*. Prognostic Utility of the Flow Cytometry and Clonality Analysis Results for Feline Lymphomas. Veterinary Sciences 2024, 11. 331.

6. Park, S.; Kim, T.Y.; Cho, B.-S.; Kwag, D.; Lee, J.-M.; Kim, M.S.; Kim, Y.; Koo, J.; Raman, A.; Kim, T.K.; Kim, H-J. Prognostic value of ELN 2022 criteria and genomic clusters using machine learning in older adults with acute myeloid leukemia. Haematologica 2023, 109, 1095-1106.

5. Park, S-S.; Lee, J.; Byun, J.M.; Choi, K.; Kim, K.H.; Lim, S.; Dingli, D.; Jeon, Y.-W.; Yahng, S.-A.; Shin, S.-H.; Min, C-K.*; Koo, J.* ML-based sequential analysis to assist selection between VMP and RD for newly diagnosed multiple myeloma. npj Precision Oncology 2023, 7, 46.

4. Koo, J.; Choi, K.; Un, N.; Lim, S. Predicting clinical outcome or prognosis of cancer treatment based on machine learning. KR PCT Patent Appl. 2021/017819, November 30, 2021.

3. Koo, J.; Choi, K.; Lee, P.; Polley, A.; Pudupakam, R.S.; Tsang, J.; Fernandez, E.; Han, E.J.; Park, S.; Swartzfager, D.; Qi, N.S.X.; Jung, M.; Ocnean, M.; Kim, H.U.; Lim, S.. Predicting dynamic clinical outcomes of the chemotherapy for canine lymphoma using a machine learning model. Vet. Sci., 2021, 8, 301.

2. Bohannan, Z.; Pudupakam, R. S.; Koo, J.; Horwitz, H.; Tsang, J.; Polley, A.; Han, J. E.; Fernandez, E.; Park, S.; Swartzfager , D.; Qi, N. S. X.; Tu, C.; Rankin, W. V.; Thamm, D. H.; Lee, H. R.; Lim, S. Predicting likelihood of in vivo chemotherapy response in canine lymphoma using ex vivo drug sensitivity and immunophenotyping data in a machine learning model. Vet. Comp. Oncol. 2021, 19, 160-171.

1. Lim, S.; Kim, J.; Koo, J.; Lee, H. Devices and methods for high-throughput screening of chemical and biochemical compounds. 2019, U.S. PCT Patent Appl. 18/44306, July 30, 2018.

Protein engineering & design

14. Cha, Y.; Choi, H.; Park, D.*; Koo, J.* Discovery of Synechocystis sp. ferredoxin with enhanced electron delivery in both biochemical and electrochemical environment. Under review.

13. Koo, J. Cell-free protein synthesis of metalloproteins. Cell-free Macromolecular Synthesis 2023, 11, 47-58.

12. Choi, G.; Kim, W.; ; Koo, J.* Investigating the performance of machine learning methods in predicting functional properties of the hydrogenase variants. Biotechnol. Bioprocess Eng. 2023, 28, 143-151.

11. Kim, S.; Koo, J.* Recent advances in utilization of ferredoxins for biosynthesis of valuable compounds. World J. Microbiol. Biotechnol. 2022, 38, 178.

10. Koo, J.*; Cha, Y. Investigation of the ferredoxin's influence on the anaerobic and aerobic, enzymatic H2 production. Front. Bioeng. Biotechnol. 2021, 9, 641305.

9. Koo, J.*; Yang, J.; Park, H. Cell-free systems: Recent advances and future prospects. Biotechnol. Bioprocess Eng. 2020, 25, 955-961.

8. Koo, J.* Enhanced aerobic H2 production by engineering an [FeFe] hydrogenase from Clostridum pasteurianum. Int. J. Hydrogen Energ. 2020, 45, 10673-10679.

7. Lu, Y.; Koo, J.* O2 sensitivity and H2 production activity of hydrogenases – A review. Biotechnol. Bioeng. 2019, 116, 3124-3135.

6. Sung, J. H.; Koo, J.; Shuler, M. L. Mimicking the human physiology with microphysiological systems. Biochip J. 2019, 13, 115-126.

5. Swartz, J.R.; Koo, J. Oxygen tolerant hydrogenase by mutating electron supply pathway. 2019, U.S. Patent 10,221,401, March 5, 2019.

4. Koo, J.; Swartz, J.R. System analysis and improved [FeFe] hydrogenase O2 tolerance suggest feasibility for photosynthetic H2 production. Metab. Eng. 2018, 49, 21-27.

3. Koo, J.; Schnabel, T.; Liong, S.; Evitt, N.H.; Swartz, J.R. High-throughput screening of catalytic H2 production. Angew. Chem. Int. Ed. 2017, 56, 1012-1016.

*Received distinction as “Hot paper”, which is given to less than 10% of the published articles within the journal.

2. Koo, J.; Shiigi, S.; Rohovie, M.; Mehta, K.; Swartz, J.R. Characterization of [FeFe] hydrogenase O2 sensitivity using a new, physiological approach. J. Biol. Chem. 2016, 291, 21563-21570.

1. Swartz, J.R.; Schnabel, T.; Koo, J. Oxygen tolerant iron-iron hydrogenase. 2015, U.S. Provisional Patent Appl. 62/215,522, September 8, 2015.

Energy system modeling & optimization

16. Jang, N..; Cho, I..; Jeon, H.; Koo, J.* Optimization of the wood pellet supply during the continued increase of the renewable energy's proportion in the energy portfolio. Korean J. Chem. Eng. 2022, 39, 2028-2035.

15. Jang, N.; Kim, W.; Lee, D.; Yoon, G.; Yang, J.; Cho, I.; Jeon, H.; Koo, J.* Cost and robustness analysis of the Korean government’s renewable energy plan under varying scenarios. Korean J. Chem. Eng. 2021, 38, 2397-2405.

14. Park, K.; Koo, J*. Optimal sizing and layout of the distributed H2 production system with safety and cost considerations. Int. J. Hydrog. Energy. 2020, 45, 34316-34325.

13. Koo, J.; Oh, S. R.; Choi, Y. U.; Jung. J.-H.; Park, K. Optimization of an organic Rankine cycle system for an LNG-powered ship. Energies. 2019, 12, 1933.

12. Kim, S.; Koo, J.; Lee, C.J.; Yoon, E.S. Optimization of Korean energy planning for sustainability considering uncertainties in learning rates and external factors. Energy. 2012, 44, 126-134.

11. Jang, N.; Koo, J.; Shin, D.; Jo, M.S.; Yoon, Y.; Yoon, E.S. Development of chemical accident database: Considerations, accident trend analysis and suggestions. Korean J. Chem. Eng. 2012, 29, 36-41.

10. Koo, J.; Park, K.; Shin, D.; Yoon, E.S. Economic evaluation of renewable energy systems under varying scenarios and its implications to Korea’s renewable energy plan. Appl. Energy. 2011, 88, 2254-2260.

9. Park, K.; Koo, J.; Shin, D.; Lee, C.J.; Yoon, E.S. Optimal multi-floor plant layout with consideration of safety distance based on mathematical programming and modified consequence analysis. Korean J. Chem. Eng. 2011, 28, 1009-1018.

8. Koo, J.; Han, K.; Yoon, E.S. Integration of CCS, emissions trading and volatilities of fuel prices into sustainable energy planning, and its robust optimization. Renew. Sustain. Energy Rev. 2011, 15, 665-672.

7. So, W.; Koo, J.; Shin, D.; Yoon, E.S. The estimation of hazardous gas release rate using optical sensor and neural network. Comp. Aided Chem. Eng. 2010, 28, 199-204.

6. Kim, Y.; So, W.; Koo, J.; Lee, G.; Yoon, E.S. Optimal Safety distance analysis for DME filling station. Proceedings of the Korean Institute of Gas Annual Symposium, 2010, 163-168.

5. Jang, N.; Han, K.; Koo, J.; Yoon, Y.; Yong, J.; Yoon, E.S. Technical Guideline on Reporting Accidents to the MARS Database Technical Guideline on Reporting Accidents to the MARS Database, 2001. J. Chem. Eng. Jpn. 2009, 42, 742-751.

4. Koo, J.; Kim, S.; Kim, H.; Kim, Y.; Yoon, E.S. A systematic approach towards accident analysis and prevention. Korean J. Chem. Eng. 2009, 26, 1476-1483.

3. Koo, J.; Kim, H.S.; So, W.; Kim, K.H.; Yoon, E.S. Safety assessment of LNG terminal focused on the consequence analysis of LNG spills. Proceedings of the 1st Annual Gas Processing Symposium, January 10-12, 2009, Doha, Qatar. Ed. Alfadala, H.E. 328-331.

2. Jang, N.; Han, K.; Koo, J.; Yoon, Y.; Yong, J.; Yoon, E.S. Development of chemical accident classification codes and tool for management in process industries. J. Chem. Eng. Jpn. 2009, 42, 742-751.

1. Koo, J.; So, W.; Jang, N.; Park, K.; Yoon, E.S. Development of an algorithm designed for analyzing risks in refueling facilities. Proceedings of the Korean Institute of Gas Annual Symposium, 2009, 136-141.

* refers to being the corresponding author of the publication.

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