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​PUBLICATIONS

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Our publications may be tracked on Google Scholar.

( * denotes equal contribution, underline denotes Yang Lab members, † denotes Yang (co-)corresponding author )

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2025

  1. Li B, Srivastava S, Shaikh M, Mereddy G, Garcia MR, Chiles EN, Shah A, Ofori-Anyinam B, Chu T, Cheney NJ, McCloskey D, Su X, Yang JH†. Bioenergetic stress potentiates antimicrobial resistance and persistence. Nat Commun. 2025; 16(1):5111.

  2. Bustad E, Petry E*, Gu O*, Griebel BT, Rustad TR, Sherman DR, Yang JH†, Ma S†. Predicting fitness in Mycobacterium tuberculosis with transcriptional regulatory network-informed interpretable machine learning. Front Tuberculosis. 2025.

  3. Yang JH†. Revealing AIEC virulence genes behind the mask of antimicrobial resistance. Cell Mol Gastroenterol Hepatol. 2025; 19(4):101465.

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2024​​

  1. Mandecki W, Chudaev M, Ye W, Wang AQ, Wilson KJ, Xu X, Kim J, Parker D, Alland D, Kumar P, Li B, Yang JH, Kreiswirth B, Mediavilla JR, Marugan JJ, Henderson MJ, Goldman E. Identification of an antibiotic from an HTS targeting EF-Tu: tRNA interaction: a prospective topical treatment for MRSA skin infections. App Environ Microbiol. 2024; e0204624.

  2. Ofori-Anyinam B, Hamblin M, Coldren ML, Li B, Mereddy G, Shaikh M, Shah A, Grady C, Ranu N, Lu S, Blainey PC, Ma S, Collins JJ, Yang JH†. Catalase activity deficiency sensitizes multidrug-resistant Mycobacterium tuberculosis to the ATP synthase inhibitor bedaquiline. Nat Commun. 2024; 15(1):9792.

  3. Wang X, Jowsey WJ, Cheung C, Smart CJ, Klaus NH, Seeto NE, Waller NJ, Chrisp MT, Peterson AL, Ofori-Anyinam B, Strong E, Nijagal B, West NP, Yang JH, Fineran PC, Cook GM, Jackson SA, McNeil MB. Whole genome CRISPRi screening identifies druggable vulnerabilities in an isoniazid resistant strain of Mycobacterium tuberculosis. Nat Commun. 2024; 15(1):9791.

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2023

  1. Rosen RS, Yang JH, Peña JS, Schloss R, Yarmush ML. An in vitro model of the macrophage-endothelial interface to characterize CAR T-cell induced cytokine storm. Sci Rep. 2023; 13:18835.

  2. Boyd JM, Esquilín-Lebrón K, Campbell CJ, Kaler KR, Norambuena J, Foley ME, Stephens TG, Rios G, Mereddy G, Zheng V, Bovermann H, Kim J, Kulczyk AW, Yang JH, Greco TM, Cristea IM, Carabetta VJ, Beavers WN, Bhattacharya D, Skaar EP, Parker D, Carroll RK, Stemmler TL. YlaN is an iron(II) binding protein that functions to relieve Fur-mediated repression of gene expression in Staphylococcus aureus. bioRxiv. 2023.

  3. Sanders LM*, Scott RT*, Yang JH, Qutub AA, Martin HG, Berrios DC, Hastings JJ, Rask J, Mackintosh G, Hoarfrost AL, Chalk S, Kalantari J, Antonsen EL, Babdor J, Barker R, Baranzini SE, Mackintosh G, Hoarfrost AL, Chalk S, Kalantari J, Beheshti A, Delgado-Aparico GM, Glicksberg BS, Greene CS, Haendel M, Hamid AA, Heller P, Jamieson D, Jarvis KJ, Komarova SV, Komorowski M, Kothiyal P, Mahabal A, Manor U, Mason CE, Matar M, Mias GI, Miller J, Myers JG, Nelson C, Oribello J, Park S, Parsons-Wingerter P, Prabhu RK, Reynolds RJ, Saravia-Butler A, Saria S, Sawyer A, Singh NK, Snyder M, Soboczenski F, Soman K, Theriot CA, Venkateswaran K, Warren L, Worthey L, Zitnik M, Costes SV. Biological research and self-driving labs in deep space supported by artificial intelligence. Nat Mach Intel. 2023; (5):208-219.

  4. Scott RT*, Sanders LM*, Antonsen EL, Hastings JJ, Park S, Mackintosh G, Reynolds RJ, Hoarfrost AL, Reynolds RJ, Hoarfrost AL, Sawyer A, Greene CS, Glicksberg BS, Theriot CA, Berrios DC, Miller J, Babdor J, Barker R, Baranzini SE, Beheshti A, Chalk S, Delgado-Aparico GM, Haendel M, Hamid AA, Heller P, Jamieson D, Jarvis KJ, Kalantari J, Khezeli K, Komarova SV, Komorowski M, Kothiyal P, Mahabal A, Manor U, Martin HG, Mason CE, Matar M, Mias GI, Myers JG, Nelson C, Oribello J, Parsons-Wingerter P, Prabhu RK, Qutub AA, Rask J, Saravia-Butler A, Saria S, Singh NK, Snyder M, Soboczenski F, Soman K, Van Valen D, Venkateswaran K, Warren L, Worthey L, Yang JH, Zitnik M, Costes SV. Biomonitoring and precision health in deep space supported by artificial intelligence. Nat Mach Intel. 2023; (5)196-207.

 

2022

  1. Kuchina A, Yang J, Aldridge B, Janes KA, Subramanian N, Krogan NJ, Bouhaddou M, Einav S, Papin J, Germain RN. How can systems approaches help us understand and treat infectious disease?. Cell Syst. 2022; 13(12):945-949.

  2. Chitale P, Lemenze AD, Fogarty EC, Shah A, Grady C, Odom-Mabey AR, Johnson WE, Yang JH, Eren AM, Brosch R, Kumar P, Alland D. A comprehensive update to the Mycobacterium tuberculosis H37Rv reference genome. Nat Commun. 2022; 13(1):7068.

  3. Bruiners N, Guerrini V, Ukey R, Dikdan RJ, Yang JH, Mishra PK, Onyuka A, Handler D, Vieth J, Carayannopoulos M, Guo S, Pollen M, Pinter A, Tyagi S, Feingold D, Philipp C, Libutti SK, Gennaro ML. Longitudinal Analysis of Biologic Correlates of COVID-19 Resolution: Case Report. Front Med. 2022; 9:91537.

  4. Yang JH. CRISP(e)R drug discovery. Nat Chem Biol. 2022; 18(5):435-436.

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2021

  1. Kim GL, Hooven TA, Norambuena J, Li B, Boyd JM, Yang JH, Parker D. Growth and stress tolerance comprise independent metabolic strategies critical for Staphylococcus aureus infection. mBio. 2021; 12(3):e0081421.

  2. Lopatkin AJ*†, Yang JH*†. Digital insights into nucleotide metabolism and antibiotic treatment failure. Front Digit Health. 2021.

  3. León-Buitimea A, Morones-Ramírez JR, Yang JH, Peña-Miller R. Editorial: Facing the upcoming of multidrug-resistant and extensively drug-resistant bacteria: novel antimicrobial therapies (NATs). Front Bioeng Biotechnol. 2021; 9:636278.

  4. Lopatkin AJ, Bening SC, Manson AL, Stokes JM, Kohanski MA, Badran AH, Earl AM, Cheney NJ, Yang JH, Collins JJ. Clinically relevant mutations in core metabolic genes confer antibiotic resistance. Science. 2021; 371(6531):eaba0862.

  5. Anahtar MN, Yang JH, Kanjilal S. Applications of machine learning to the problem of antimicrobial resistance: An emerging model for translational research. J Clin Microbiol. 2021; 59(7):e0126020.

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——— BEFORE RUTGERS NEW JERSEY MEDICAL SCHOOL ———

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2019

  1. Lopatkin AJ, Stokes JM, Zheng EJ, Yang JH, Takahashi MK, You L, Collins JJ. Bacterial metabolic state more accurately predicts antibiotic lethality than growth rate. Nat Microbiol. 2019; 4(12):2109-2117.

  2. Yang JH, Wright SN*, Hamblin M*, McCloskey D, Alcantar MA, Schrübbers L, Lopatkin AJ, Satish S, Nili A, Palsson BO, Walker GC, Collins JJ. A white-box machine learning approach for revealing antibiotic mechanisms of action. Cell. 2019; 177(6):1649-1661.

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2017

  1. Yang JH*, Bhargava P*, McCloskey D, Mao N, Palsson BO, Collins JJ. Antibiotic-induced changes to the host metabolic environment inhibit drug efficacy and alter immune function. Cell Host Microbe. 2017; 22(6):757-765.

  2. Yang JH*, Bening SC*, Collins JJ. Antibiotic efficacy – context matters. Curr Opin Microbiol. 2017; 39:73-80.

  3. Takahashi N*, Gruber CC*, Yang JH, Liu X, Braff D, Yashaswini C, Bhubhani S, Furuta Y, Andreescu S, Collins JJ, Walker GC. Lethality of MalE-LacZ hybrid protein shares mechanistic attributes with oxidative component of antibiotic lethality. Proc Natl Acad Sci U S A. 2017; 114(34):9164-9169.

  4. Meylan S, Porter CB*, Yang JH*, Belenky P, Gutierrez A, Lobritz MA, Park J, Kim S, Moskowitz S, Collins JJ. Carbon sources tune antibiotic susceptibility in Pseudomonas aeruginosa via Tricarboxylic acid cycle control. Cell Chem Biol. 2017; 24(2):195-206.

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2015

  1. Lobritz MA*, Belenky P*, Porter CBM, Gutierrez A, Yang JH, Schwarz EG, Dwyer DJ, Khalil AS, Collins JJ. Antibiotic efficacy is linked to bacterial cellular respiration. Proc Natl Acad Sci U S A. 2015; 112(27):8173-80.

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2014

  1. Dwyer DJ*, Belenky PA*, Yang JH*, MacDonald IC, Martell JD, Takahashi N, Chan CT, Lobritz MA, Braff D, Schwarz EG, Ye JD, Pati M, Vercruysse M, Ralifo PS, Allison KR, Khalil AS, Ting AY, Walker GC, Collins JJ. Antibiotics induce redox-related physiological alterations as part of their lethality. Proc Natl Acad Sci U S A. 2014; 111(20):E2100-9.

  2. Yang JH, Polanowska-Grabowska RK, Smith JS, Shields CW, Saucerman JJ. PKA catalytic subunit compartmentation regulates contractile and hypertrophic responses to β-adrenergic signaling. J Mol Cell Cardiol. 2014; 66:83-93.

 

2012

  1. Yang JH, Saucerman JJ. Phospholemman is a negative feed-forward regulator of Ca2+ in β-adrenergic signaling, accelerating β-adrenergic inotropy. J Mol Cell Cardiol. 2012; 52(5):1048-55.

  2. Sample V*, DiPilato LM*, Yang JH*, Ni Q, Saucerman JJ, Zhang J. Regulation of nuclear PKA revealed by spatiotemporal manipulation of cAMP. Nat Chem Biol. 2012; 8(4):375-82.

 

2011

  1. Yang JH, Saucerman JJ. Computational models reduce complexity and accelerate insight into cardiac signaling networks. Circ Res. 2011; 108(01):85-97.

  2. Benedict KF, Mac Gabhann F*, Amanfu RK*, Chavali AK*, Gianchandani EP*, Glaw LS*, Oberhardt MA*, Thorne BC*, Yang JH*, Papin JA, Peirce SM, Saucerman JJ, Skalak TC. Systems analysis of bounded signaling modules generates experimental roadmap for eight major diseases. Ann Biomed Eng. 2011; 39(2):621-35.

 

2009

  1. Yang J. Science Careers: Where does advocacy fit? Science. 2009; 323(5911):208-209.

 

2005

  1. Gurewitsch ED, Kim EJ, Yang JH, Outland KE, McDonald MK, Allen RH. Comparing McRoberts’ and Rubin’s maneuvers for initial management of shoulder dystocia: An objective evaluation. Am J Obstet Gynecol. 2005; 192(1):153-160.

 

2004

  1. Kim EJ, Allen RH, Yang JH, McDonald MK, Tam W, Gurewitsch ED. Simulating complicated human birth for research and training. Conf Proc IEEE Eng Med Biol Soc. 2004; 4:2762-6.

 

2003

  1. Gurewitsch E, Kim E, Yang J, Outland K, Allen R. An objective evaluation of McRoberts’ and Rubin’s maneuvers for shoulder dystocia. Am J Obstet Gynecol. 2003; 189(6):S208.

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