• 2019

  1. Alfatah M, Wong JH, Kong KW, Utama F, Hoon S, Arumugam P. (2019). Chemical-genetic interaction landscape of mono-(2-ethylhexyl)-phthalate using chemogenomic profiling in yeast. Chemosphere 2019; 228:219-231.
  2. Alfatah M, Wong JH, Nge CE, Kong KW, Low KN, Leong CY, Crasta S, Munusamy M, Chang AML, Hoon S, Ng SB, Yoganathan K, Arumugam P.  (2019).  Hypoculoside, a sphingoid base-like compound from Acremonium disrupts the membrane integrity of yeast cells.  Sci Rep. 2019;9(1):710.
  3. Chan JCY, Tan SPF, Upton Z, Chan ECY. (2019). Bottom-up Physiologically-Based Biokinetic Modelling as an Alternative to Animal Testing. Alternatives to Animal Experimentation (ALTEX).
  4. Krutz NL, Winget J, Ryan CA, Wimalasena R, Maurer-Stroh S, Dearman RJ, Kimber I, Gerberick GF. (2019). Proteomic and bioinformatic analyses for the identification of proteins with low allergenic potential for hazard assessment. Toxicol Sci. 2019 Mar 23. pii: kfz078.
  5. Maurer-Stroh S, Krutz NL, Kern PS, Gunalan V, Nguyen MN, Limviphuvadh V, Eisenhaber F, Gerberick GF. (2019). AllerCatPro – Prediction of protein allergenicity potential from the protein sequence. Bioinformatics. 2019 Jan 18. doi: 10.1093/bioinformatics/btz029. [Epub ahead of print].
  6. Nguyen MN, Sen N, Lin M, Joseph TL, Vaz C, Tanavde V, Way L, Hupp T, Verma CS, Madhusudhan MS. (2019). Discovering Putative Protein Targets of Small Molecules: A Study of the p53 Activator Nutlin.  J Chem Inf Model. 2019 Mar 8.
  7. Sinha S, Nge CE, Leong CY, Ng V, Crasta S, Alfatah M, Goh F, Low KN, Zhang H, Arumugam P, Lezhava A, Chen SL, Yoganathan K, Ng SB, Eisenhaber F, Eisenhaber B. (2019). Genomics-driven discovery of a biosynthetic gene cluster required for the synthesis of BII-Rafflesfungin from the fungus Phoma sp. F3723. BMC Genomics 2019;20:374.
  8. Wong JH, Alfatah M, Kong KW, Hoon S, Yeo WL, Ching KC, Goh CJH, Zhang MM, Lim YH, Fong FT, Arumugam P. (2019). Chemogenomic profiling in yeast reveals mode-of-action of polyene macrolactam antibiotic auroramycin.PLoS ONE 2019; 14(6): e0218189.

  • 2018

  1. Lee CZW, Kozaki T, and Ginhoux F. (2018). Studying tissue macrophages in vitro: are iPSC-derived cells the answer? Nat Rev Immunol., 18(11):716-725. DOI: 10.1038/s41577-018-0054-y.
  2. Lee JJ, Miller JA, Basu S, Kee TV, Loo LH. (2018). Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence. Archives of Toxicology, 92(6):2055-2075.
  3. Lim VJY, Du W, Chen YZ, Fan H. (2018). A benchmarking study on virtual ligand screening against homology models of human GPCRs. Proteins. 2018 Sep;86(9):978-989.
  4. Lim YT, Prabhu N, Dai L, Go KD, Chen D, Sreekumar L, Egeblad L, Eriksson S, Chen L, Veerappan S, Teo HL, Tan CSH, Lengqvist J, Larsson A, Sobota RM, Nordlund P. (2018). An efficient proteome-wide strategy for discovery and characterization of cellular nucleotide-protein interactions. PLOS ONE 12 (12):e0208273.
  5. Limviphuvadh V, Tan CS, Konishi F, Jenjaroenpun P, Xiang JS, Kremenska Y, Mu YS, Syn N, Lee SC, Soo RA, Eisenhaber F, Maurer-Stroh S, Yong WP. (2018). Discovering novel SNPs that are correlated with patient outcome in a Singaporean cancer patient cohort treated with gemcitabine-based chemotherapy. BMC Cancer. 2018 May 11;18(1):555.
  6. Ng SB, Yoganathan K, Fan H, Arumugam P, Eisenhaber B, Eisenhaber F. (2018).  The 160K Natural Organism Library, a unique resource for natural products research. Nat Biotechnol. 2018;36(7):570-573.
  7. Ng SMS, Yap JM, Lau QY, Ng FM, Ong EHQ, Barkham T, Teo JWP, Alfatah M, Kong KW, Hoon S, Arumugam P, Hill J, Brian Chia CS. (2018). Structure-activity relationship studies of ultra-short peptides with potent activities against fluconazole-resistant Candida albicans. Eur J Med Chem. 2018;150:479-490.
  8. Tan CSH#, Go KD, Bisteau X, Dai L, Yong CH, Prabhu N, Ozturk MB, Lim YT, Sreekumar L, Lengqvist J, Tergaonkar V, Kaldis P, Sobota RM, Nordlund P. (2018). Thermal Proximity Co-aggregation for System-wide Profiling of Protein Complex Dynamics in Cells.  Science. 359 (6380):1170-1177. 
    · Highlighted in Science 359 (6380):1105-1106, Nature Method 15 (4):242-243, Cell Systems 6 (3), F1000Prime, GenomeWeb (9th Feb 2018),  PHYS.ORG and Nature INDEX.
  9. Tasnim F, Xing J, Huang X, Mo S, Wei X, Tan MH, and Yu H. (2018). Generation of Mature Kupffer Cells from Human Induced Pluripotent Stem Cells. Biomaterials, 192: 337-391. DOI: 10.1016/j.biomaterials.2018.11.016
  10. Yu Y, Ananthanarayanan A, Singh NH, Hong X, Sakban R, Mittal N, Luo X, Robens J, Xia L, McMillian M, and Yu H. (2018). TGFβ1-mediated suppression of Cytochrome P450(CYP) induction responses in rat hepatocyte-fibroblast co-cultures. Toxicology In Vitro, 50: 47-53. DOI: 10.1016/j.tiv.2018.01.015

  • 2017

  1. Bougen-Zhukov N, Loh SY, Lee HK, Loo LH. (2017) Large-scale image-based screening and profiling of cellular phenotypes. Cytometry Part A, 91A:115-125.
  2. Loo LH and Zink D. (2017). High-throughput prediction of nephrotoxicity in humans. Alternatives to Laboratory Animals, 45:241-252.
  3. Mohebiany AN and Waisman A. (2017). Upgrading from iMac to iMicro. Immunity, 18; 47(1):10-12. DOI: 10.1016/j.immuni.2017.07.001.
  4. Takata K, Kozaki T, Lee CZW, Thion MS, Otsuka M, Lim S, Utami KH, Fidan K, Park DS, et al. (2017). Induced-Pluripotent-Stem-Cell-Derived Primitive Macrophages Provide a Platform for Modeling Tissue-Resident Macrophage Differentiation and Function. Immunity, 47(1):183-198.e6. DOI: 10.1016/j.immuni.2017.06.017.
  5. Wong JC, Zidar J, Ho J, Wang Y, Lee KK, Zheng J, Sullivan MB, You X. (2017). Assessment of several machine learning methods towards reliable prediction of hormone receptor binding affinity. Chemical Data Collections 9, 114-124.
  6. Xing J, Cao Y, Yu Y, Li H, Song Z, Yu H. (2017). In Vitro Micropatterned Human Pluripotent Stem Cell Test (µP-hPST) for Morphometric-Based Teratogen Screening. Sci Rep. 2017; 7:8491.