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Connection

Co-Authors

This is a "connection" page, showing publications co-authored by Richard Baker and Christopher Sassetti.
Connection Strength

1.647
  1. Koh EI, Oluoch PO, Ruecker N, Proulx MK, Soni V, Murphy KC, Papavinasasundaram K, Reames CJ, Trujillo C, Zaveri A, Zimmerman MD, Aslebagh R, Baker RE, Shaffer SA, Guinn KM, Fitzgerald M, Dartois V, Ehrt S, Hung DT, Ioerger TR, Rubin EJ, Rhee KY, Schnappinger D, Sassetti CM. Chemical-genetic interaction mapping links carbon metabolism and cell wall structure to tuberculosis drug efficacy. Proc Natl Acad Sci U S A. 2022 04 12; 119(15):e2201632119.
    View in: PubMed
    Score: 0.205
  2. Smith CM, Baker RE, Proulx MK, Mishra BB, Long JE, Park SW, Lee HN, Kiritsy MC, Bellerose MM, Olive AJ, Murphy KC, Papavinasasundaram K, Boehm FJ, Reames CJ, Meade RK, Hampton BK, Linnertz CL, Shaw GD, Hock P, Bell TA, Ehrt S, Schnappinger D, Pardo-Manuel de Villena F, Ferris MT, Ioerger TR, Sassetti CM. Host-pathogen genetic interactions underlie tuberculosis susceptibility in genetically diverse mice. Elife. 2022 02 03; 11.
    View in: PubMed
    Score: 0.203
  3. Bellerose MM, Proulx MK, Smith CM, Baker RE, Ioerger TR, Sassetti CM. Distinct Bacterial Pathways Influence the Efficacy of Antibiotics against Mycobacterium tuberculosis. mSystems. 2020 Aug 04; 5(4).
    View in: PubMed
    Score: 0.183
  4. Smith CM, Proulx MK, Lai R, Kiritsy MC, Bell TA, Hock P, Pardo-Manuel de Villena F, Ferris MT, Baker RE, Behar SM, Sassetti CM. Functionally Overlapping Variants Control Tuberculosis Susceptibility in Collaborative Cross Mice. mBio. 2019 11 26; 10(6).
    View in: PubMed
    Score: 0.174
  5. Bellerose MM, Baek SH, Huang CC, Moss CE, Koh EI, Proulx MK, Smith CM, Baker RE, Lee JS, Eum S, Shin SJ, Cho SN, Murray M, Sassetti CM. Common Variants in the Glycerol Kinase Gene Reduce Tuberculosis Drug Efficacy. mBio. 2019 07 30; 10(4).
    View in: PubMed
    Score: 0.170
  6. Rittershaus ESC, Baek SH, Krieger IV, Nelson SJ, Cheng YS, Nambi S, Baker RE, Leszyk JD, Shaffer SA, Sacchettini JC, Sassetti CM. A Lysine Acetyltransferase Contributes to the Metabolic Adaptation to Hypoxia in Mycobacterium tuberculosis. Cell Chem Biol. 2018 12 20; 25(12):1495-1505.e3.
    View in: PubMed
    Score: 0.161
  7. Mishra BB, Lovewell RR, Olive AJ, Zhang G, Wang W, Eugenin E, Smith CM, Phuah JY, Long JE, Dubuke ML, Palace SG, Goguen JD, Baker RE, Nambi S, Mishra R, Booty MG, Baer CE, Shaffer SA, Dartois V, McCormick BA, Chen X, Sassetti CM. Nitric oxide prevents a pathogen-permissive granulocytic inflammation during tuberculosis. Nat Microbiol. 2017 May 15; 2:17072.
    View in: PubMed
    Score: 0.146
  8. Smith CM, Proulx MK, Olive AJ, Laddy D, Mishra BB, Moss C, Gutierrez NM, Bellerose MM, Barreira-Silva P, Phuah JY, Baker RE, Behar SM, Kornfeld H, Evans TG, Beamer G, Sassetti CM. Tuberculosis Susceptibility and Vaccine Protection Are Independently Controlled by Host Genotype. mBio. 2016 09 20; 7(5).
    View in: PubMed
    Score: 0.140
  9. Long JE, DeJesus M, Ward D, Baker RE, Ioerger T, Sassetti CM. Identifying essential genes in Mycobacterium tuberculosis by global phenotypic profiling. Methods Mol Biol. 2015; 1279:79-95.
    View in: PubMed
    Score: 0.124
  10. Kurtz SL, Baker RE, Boehm FJ, Lehman CC, Mittereder LR, Khan H, Rossi AP, Gatti DM, Beamer G, Sassetti CM, Elkins KL. Multiple genetic loci influence vaccine-induced protection against Mycobacterium tuberculosis in genetically diverse mice. PLoS Pathog. 2024 Mar; 20(3):e1012069.
    View in: PubMed
    Score: 0.059
  11. Subramaniyam S, DeJesus MA, Zaveri A, Smith CM, Baker RE, Ehrt S, Schnappinger D, Sassetti CM, Ioerger TR. Statistical analysis of variability in TnSeq data across conditions using zero-inflated negative binomial regression. BMC Bioinformatics. 2019 Nov 21; 20(1):603.
    View in: PubMed
    Score: 0.044
  12. DeJesus MA, Nambi S, Smith CM, Baker RE, Sassetti CM, Ioerger TR. Statistical analysis of genetic interactions in Tn-Seq data. Nucleic Acids Res. 2017 Jun 20; 45(11):e93.
    View in: PubMed
    Score: 0.037
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.