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Personalized Evaluation of Biomarker Value: A Cost-Benefit Perspective.

Statistics in biosciences

Huang Y, Laber E.
PMID: 27446505
Stat Biosci. 2016;8:43-65. doi: 10.1007/s12561-014-9122-4. Epub 2014 Nov 21.

For a patient who is facing a treatment decision, the added value of information provided by a biomarker depends on the individual patient's expected response to treatment with and without the biomarker, as well as his/her tolerance of disease...

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Huang Y, Laber E. Personalized Evaluation of Biomarker Value: A Cost-Benefit Perspective. Stat Biosci. 2014;8:43-65doi: 10.1007/s12561-014-9122-4.
Huang, Y., & Laber, E. (2016). Personalized Evaluation of Biomarker Value: A Cost-Benefit Perspective. Statistics in biosciences, 843-65. https://doi.org/10.1007/s12561-014-9122-4
Huang, Ying, and Laber, Eric. "Personalized Evaluation of Biomarker Value: A Cost-Benefit Perspective." Statistics in biosciences vol. 8 (2016): 43-65. doi: https://doi.org/10.1007/s12561-014-9122-4
Huang Y, Laber E. Personalized Evaluation of Biomarker Value: A Cost-Benefit Perspective. Stat Biosci. 2016;8:43-65. doi: 10.1007/s12561-014-9122-4. Epub 2014 Nov 21. PMID: 27446505; PMCID: PMC4938856.
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Structured detection of interactions with the directed lasso.

Statistics in biosciences

Pashova H, LeBlanc M, Kooperberg C.
PMID: 29292402
Stat Biosci. 2017 Dec;9(2):676-691. doi: 10.1007/s12561-016-9184-6. Epub 2016 Nov 29.

When considering low-dimensional gene-treatment or gene-environment interactions we might suspect groups of genes to interact with treatment or environment in a similar way. For example, genes associated with related biological processes might interact with an environmental factor or a...

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Pashova H, LeBlanc M, Kooperberg C. Structured detection of interactions with the directed lasso. Stat Biosci. 2016;9(2):676-691doi: 10.1007/s12561-016-9184-6.
Pashova, H., LeBlanc, M., & Kooperberg, C. (2017). Structured detection of interactions with the directed lasso. Statistics in biosciences, 9(2), 676-691. https://doi.org/10.1007/s12561-016-9184-6
Pashova, Hristina, et al. "Structured detection of interactions with the directed lasso." Statistics in biosciences vol. 9,2 (2017): 676-691. doi: https://doi.org/10.1007/s12561-016-9184-6
Pashova H, LeBlanc M, Kooperberg C. Structured detection of interactions with the directed lasso. Stat Biosci. 2017 Dec;9(2):676-691. doi: 10.1007/s12561-016-9184-6. Epub 2016 Nov 29. PMID: 29292402; PMCID: PMC5747322.
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Cooperating H3N2 Influenza Virus Variants Are Not Detectable in Primary Clinical Samples.

mSphere

Xue KS, Greninger AL, Pérez-Osorio A, Bloom JD.
PMID: 29299533
mSphere. 2018 Jan 03;3(1). doi: 10.1128/mSphereDirect.00552-17. eCollection 2018.

The high mutation rates of RNA viruses lead to rapid genetic diversification, which can enable cooperative interactions between variants in a viral population. We previously described two distinct variants of H3N2 influenza virus that cooperate in cell culture. These...

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Xue KS, Greninger AL, Pérez-Osorio A, et al. Cooperating H3N2 Influenza Virus Variants Are Not Detectable in Primary Clinical Samples. mSphere. 2018;3(1)doi: 10.1128/mSphereDirect.00552-17.
Xue, K. S., Greninger, A. L., Pérez-Osorio, A., & Bloom, J. D. (2018). Cooperating H3N2 Influenza Virus Variants Are Not Detectable in Primary Clinical Samples. mSphere, 3(1), . https://doi.org/10.1128/mSphereDirect.00552-17
Xue, Katherine S, et al. "Cooperating H3N2 Influenza Virus Variants Are Not Detectable in Primary Clinical Samples." mSphere vol. 3,1 (2018). doi: https://doi.org/10.1128/mSphereDirect.00552-17
Xue KS, Greninger AL, Pérez-Osorio A, Bloom JD. Cooperating H3N2 Influenza Virus Variants Are Not Detectable in Primary Clinical Samples. mSphere. 2018 Jan 03;3(1). doi: 10.1128/mSphereDirect.00552-17. eCollection 2018. PMID: 29299533; PMCID: PMC5750391.
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Whole-genome sequencing of esophageal adenocarcinoma in Chinese patients reveals distinct mutational signatures and genomic alterations.

Communications biology

Dai JY, Wang X, Buas MF, Zhang C, Ma J, Wei B, Li Y, Zhao B, Hyun TS, Chen X, Loeb KR, Odze R, Yao L, Sun X, Self S, Vaughan TL, Guo Y.
PMID: 30374464
Commun Biol. 2018 Oct 24;1:174. doi: 10.1038/s42003-018-0182-8. eCollection 2018.

While the incidence of esophageal adenocarcinoma (EAC) has risen drastically in Western countries over the last 40 years, a similar trend has not been observed for EAC in China. Here, we analyzed mutational spectrum, copy number alterations, and structural...

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Dai JY, Wang X, Buas MF, et al. Whole-genome sequencing of esophageal adenocarcinoma in Chinese patients reveals distinct mutational signatures and genomic alterations. Commun Biol. 2018;1:174doi: 10.1038/s42003-018-0182-8.
Dai, J. Y., Wang, X., Buas, M. F., Zhang, C., Ma, J., Wei, B., Li, Y., Zhao, B., Hyun, T. S., Chen, X., Loeb, K. R., Odze, R., Yao, L., Sun, X., Self, S., Vaughan, T. L., & Guo, Y. (2018). Whole-genome sequencing of esophageal adenocarcinoma in Chinese patients reveals distinct mutational signatures and genomic alterations. Communications biology, 1174. https://doi.org/10.1038/s42003-018-0182-8
Dai, James Y, et al. "Whole-genome sequencing of esophageal adenocarcinoma in Chinese patients reveals distinct mutational signatures and genomic alterations." Communications biology vol. 1 (2018): 174. doi: https://doi.org/10.1038/s42003-018-0182-8
Dai JY, Wang X, Buas MF, Zhang C, Ma J, Wei B, Li Y, Zhao B, Hyun TS, Chen X, Loeb KR, Odze R, Yao L, Sun X, Self S, Vaughan TL, Guo Y. Whole-genome sequencing of esophageal adenocarcinoma in Chinese patients reveals distinct mutational signatures and genomic alterations. Commun Biol. 2018 Oct 24;1:174. doi: 10.1038/s42003-018-0182-8. eCollection 2018. PMID: 30374464; PMCID: PMC6200836.
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Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral sequence divergence.

Virus evolution

Hilton SK, Bloom JD.
PMID: 30425841
Virus Evol. 2018 Nov 06;4(2):vey033. doi: 10.1093/ve/vey033. eCollection 2018 Jul.

Molecular phylogenetics is often used to estimate the time since the divergence of modern gene sequences. For highly diverged sequences, such phylogenetic techniques sometimes estimate surprisingly recent divergence times. In the case of viruses, independent evidence indicates that the...

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Hilton SK, Bloom JD. Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral sequence divergence. Virus Evol. 2018;4(2):vey033doi: 10.1093/ve/vey033.
Hilton, S. K., & Bloom, J. D. (2018). Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral sequence divergence. Virus evolution, 4(2), vey033. https://doi.org/10.1093/ve/vey033
Hilton, Sarah K, and Bloom, Jesse D. "Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral sequence divergence." Virus evolution vol. 4,2 (2018): vey033. doi: https://doi.org/10.1093/ve/vey033
Hilton SK, Bloom JD. Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral sequence divergence. Virus Evol. 2018 Nov 06;4(2):vey033. doi: 10.1093/ve/vey033. eCollection 2018 Jul. PMID: 30425841; PMCID: PMC6220371.
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Response to Guo et al.'s Letter to the Editor.

Biostatistics (Oxford, England)

Fong Y, Huang Y, Lemos MP, Mcelrath MJ.
PMID: 30590447
Biostatistics. 2019 Apr 01;20(2):363-365. doi: 10.1093/biostatistics/kxy061.

No abstract available.

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Fong Y, Huang Y, Lemos MP, et al. Response to Guo et al.'s Letter to the Editor. Biostatistics. 2019;20(2):363-365doi: 10.1093/biostatistics/kxy061.
Fong, Y., Huang, Y., Lemos, M. P., & Mcelrath, M. J. (2019). Response to Guo et al.'s Letter to the Editor. Biostatistics (Oxford, England), 20(2), 363-365. https://doi.org/10.1093/biostatistics/kxy061
Fong, Youyi, et al. "Response to Guo et al.'s Letter to the Editor." Biostatistics (Oxford, England) vol. 20,2 (2019): 363-365. doi: https://doi.org/10.1093/biostatistics/kxy061
Fong Y, Huang Y, Lemos MP, Mcelrath MJ. Response to Guo et al.'s Letter to the Editor. Biostatistics. 2019 Apr 01;20(2):363-365. doi: 10.1093/biostatistics/kxy061. PMID: 30590447; PMCID: PMC6657390.
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Linking influenza virus evolution within and between human hosts.

Virus evolution

Xue KS, Bloom JD.
PMID: 32082616
Virus Evol. 2020 Feb 17;6(1):veaa010. doi: 10.1093/ve/veaa010. eCollection 2020 Jan.

Influenza viruses rapidly diversify within individual human infections. Several recent studies have deep-sequenced clinical influenza infections to identify viral variation within hosts, but it remains unclear how within-host mutations fare at the between-host scale. Here, we compare the genetic...

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Xue KS, Bloom JD. Linking influenza virus evolution within and between human hosts. Virus Evol. 2020;6(1):veaa010doi: 10.1093/ve/veaa010.
Xue, K. S., & Bloom, J. D. (2020). Linking influenza virus evolution within and between human hosts. Virus evolution, 6(1), veaa010. https://doi.org/10.1093/ve/veaa010
Xue, Katherine S, and Bloom, Jesse D. "Linking influenza virus evolution within and between human hosts." Virus evolution vol. 6,1 (2020): veaa010. doi: https://doi.org/10.1093/ve/veaa010
Xue KS, Bloom JD. Linking influenza virus evolution within and between human hosts. Virus Evol. 2020 Feb 17;6(1):veaa010. doi: 10.1093/ve/veaa010. eCollection 2020 Jan. PMID: 32082616; PMCID: PMC7025719.
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A comparative study of topology-based pathway enrichment analysis methods.

BMC bioinformatics

Ma J, Shojaie A, Michailidis G.
PMID: 31684881
BMC Bioinformatics. 2019 Nov 04;20(1):546. doi: 10.1186/s12859-019-3146-1.

BACKGROUND: Pathway enrichment extensively used in the analysis of Omics data for gaining biological insights into the functional roles of pre-defined subsets of genes, proteins and metabolites. A large number of methods have been proposed in the literature for...

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Ma J, Shojaie A, Michailidis G. A comparative study of topology-based pathway enrichment analysis methods. BMC Bioinformatics. 2019;20(1):546doi: 10.1186/s12859-019-3146-1.
Ma, J., Shojaie, A., & Michailidis, G. (2019). A comparative study of topology-based pathway enrichment analysis methods. BMC bioinformatics, 20(1), 546. https://doi.org/10.1186/s12859-019-3146-1
Ma, Jing, et al. "A comparative study of topology-based pathway enrichment analysis methods." BMC bioinformatics vol. 20,1 (2019): 546. doi: https://doi.org/10.1186/s12859-019-3146-1
Ma J, Shojaie A, Michailidis G. A comparative study of topology-based pathway enrichment analysis methods. BMC Bioinformatics. 2019 Nov 04;20(1):546. doi: 10.1186/s12859-019-3146-1. PMID: 31684881; PMCID: PMC6829999.
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Doubly robust nonparametric inference on the average treatment effect.

Biometrika

Benkeser D, Carone M, Laan MJV, Gilbert PB.
PMID: 29430041
Biometrika. 2017 Dec;104(4):863-880. doi: 10.1093/biomet/asx053. Epub 2017 Oct 16.

Doubly robust estimators are widely used to draw inference about the average effect of a treatment. Such estimators are consistent for the effect of interest if either one of two nuisance parameters is consistently estimated. However, if flexible, data-adaptive...

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Benkeser D, Carone M, Laan MJV, et al. Doubly robust nonparametric inference on the average treatment effect. Biometrika. 2017;104(4):863-880doi: 10.1093/biomet/asx053.
Benkeser, D., Carone, M., Laan, M. J. V., & Gilbert, P. B. (2017). Doubly robust nonparametric inference on the average treatment effect. Biometrika, 104(4), 863-880. https://doi.org/10.1093/biomet/asx053
Benkeser, D, et al. "Doubly robust nonparametric inference on the average treatment effect." Biometrika vol. 104,4 (2017): 863-880. doi: https://doi.org/10.1093/biomet/asx053
Benkeser D, Carone M, Laan MJV, Gilbert PB. Doubly robust nonparametric inference on the average treatment effect. Biometrika. 2017 Dec;104(4):863-880. doi: 10.1093/biomet/asx053. Epub 2017 Oct 16. PMID: 29430041; PMCID: PMC5793673.
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On Estimation of the Hazard Function from Population-based Case-Control Studies.

Journal of the American Statistical Association

Hsu L, Gorfine M, Zucker DM.
PMID: 30906082
J Am Stat Assoc. 2018;113(522):560-570. doi: 10.1080/01621459.2017.1356315. Epub 2018 Jun 12.

The population-based case-control study design has been widely used for studying the etiology of chronic diseases. It is well established that the Cox proportional hazards model can be adapted to the case-control study and hazard ratios can be estimated...

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Hsu L, Gorfine M, Zucker DM. On Estimation of the Hazard Function from Population-based Case-Control Studies. J Am Stat Assoc. 2018;113(522):560-570doi: 10.1080/01621459.2017.1356315.
Hsu, L., Gorfine, M., & Zucker, D. M. (2018). On Estimation of the Hazard Function from Population-based Case-Control Studies. Journal of the American Statistical Association, 113(522), 560-570. https://doi.org/10.1080/01621459.2017.1356315
Hsu, Li, et al. "On Estimation of the Hazard Function from Population-based Case-Control Studies." Journal of the American Statistical Association vol. 113,522 (2018): 560-570. doi: https://doi.org/10.1080/01621459.2017.1356315
Hsu L, Gorfine M, Zucker DM. On Estimation of the Hazard Function from Population-based Case-Control Studies. J Am Stat Assoc. 2018;113(522):560-570. doi: 10.1080/01621459.2017.1356315. Epub 2018 Jun 12. PMID: 30906082; PMCID: PMC6428431.
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phydms: software for phylogenetic analyses informed by deep mutational scanning.

PeerJ

Hilton SK, Doud MB, Bloom JD.
PMID: 28785526
PeerJ. 2017 Jul 31;5:e3657. doi: 10.7717/peerj.3657. eCollection 2017.

It has recently become possible to experimentally measure the effects of all amino-acid point mutations to proteins using deep mutational scanning. These experimental measurements can inform site-specific phylogenetic substitution models of gene evolution in nature. Here we describe software...

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Hilton SK, Doud MB, Bloom JD. phydms: software for phylogenetic analyses informed by deep mutational scanning. PeerJ. 2017;5:e3657doi: 10.7717/peerj.3657.
Hilton, S. K., Doud, M. B., & Bloom, J. D. (2017). phydms: software for phylogenetic analyses informed by deep mutational scanning. PeerJ, 5e3657. https://doi.org/10.7717/peerj.3657
Hilton, Sarah K, et al. "phydms: software for phylogenetic analyses informed by deep mutational scanning." PeerJ vol. 5 (2017): e3657. doi: https://doi.org/10.7717/peerj.3657
Hilton SK, Doud MB, Bloom JD. phydms: software for phylogenetic analyses informed by deep mutational scanning. PeerJ. 2017 Jul 31;5:e3657. doi: 10.7717/peerj.3657. eCollection 2017. PMID: 28785526; PMCID: PMC5541924.
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Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition.

Journal of causal inference

Gilbert PB, Gabriel EE, Huang Y, Chan IS.
PMID: 26722639
J Causal Inference. 2015 Sep 01;3(2):157-175. doi: 10.1515/jci-2014-0007. Epub 2015 Feb 01.

A common problem of interest within a randomized clinical trial is the evaluation of an inexpensive response endpoint as a valid surrogate endpoint for a clinical endpoint, where a chief purpose of a valid surrogate is to provide a...

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Gilbert PB, Gabriel EE, Huang Y, et al. Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition. J Causal Inference. 2015;3(2):157-175doi: 10.1515/jci-2014-0007.
Gilbert, P. B., Gabriel, E. E., Huang, Y., & Chan, I. S. (2015). Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition. Journal of causal inference, 3(2), 157-175. https://doi.org/10.1515/jci-2014-0007
Gilbert, Peter B, et al. "Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition." Journal of causal inference vol. 3,2 (2015): 157-175. doi: https://doi.org/10.1515/jci-2014-0007
Gilbert PB, Gabriel EE, Huang Y, Chan IS. Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition. J Causal Inference. 2015 Sep 01;3(2):157-175. doi: 10.1515/jci-2014-0007. Epub 2015 Feb 01. PMID: 26722639; PMCID: PMC4692254.
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Showing 1 to 12 of 30 entries