News
Faculty Awarded Grants
Assistant Professor Nabihah Tayob received an R01 grant to support her research, “Biomarker Screening Algorithms for the Improved Early Detection of Hepatocellular Carcinoma.”
Professor Xuelin Huang received grant funding as Co-director of the Biostatistics/Bioinformatics Core for The University of Texas MD Anderson Cancer Center SPORE 2P50CA100632-16 (NIH/NCI), in coordination with PI Hagop Kantarjian, for the proposed research goal of discovering/enhancing new therapies through a better understanding of the causal pathophysiologies in leukemia and the identification of actionable targets.
Professor Liang Li was awarded two R01 grants from NCI to support the following research: “Estimating the Cost Trajectories and Projecting the Cost of Cancer Care in the United States: Methodology and Application" and “Dynamic Prediction of Renal Failure Using Longitudinal Prognostic Information Among Patients with Chronic Kidney Disease and Kidney Transplant.”
Assistant Professor Christine Peterson has received grant funding from the National Science Foundation for her proposed research, “Collaborative research: Bayesian network estimation across multiple sample groups and data types.”
Assistant Professor Min Jin Ha has been awarded an NIH R21 grant for her proposed research, “Proteomic-based integrated subject-specific networks in cancer.”
Assistant Professor Suyu Liu has received a grant award from the American Cancer Society for her proposed research, “Bayesian adaptive designs for early phase clinical trials of immunotherapy.”
MD ANDERSON BIOSTATISTICS AT ENAR 2019 SPRING MEETING
Faculty, analysts, postdoctoral fellows and graduate researchers from the Biostatistics department organized sessions, gave presentations, and/or had coauthored work presented at ENAR 2019 in Philadelphia, Pennsylvania, USA, March 24-27, 2019.
ENAR Invited Sessions
Liang Li (speaker): Dynamic Prediction of Competing Risk Events using Landmark Sub-Distribution Hazard Model with Multivariate Longitudinal Biomarkers. Jeffrey S. Morris (speaker), Hojin Yang, Michelle Miranda, etc.: Bayesian Regression Models for Big Spatially or Longitudinally Correlated Functional Data. Peter F. Thall, etc.: Bayesian Variable Selection for a Semi-Competing Risks Model with Three Hazard Functions. Ying Yuan (speaker): A Bayesian Adaptive Design for Biosimilar Clinical Trials Using Calibrated Power Prior.
ENAR Contributed Sessions
Jing Ning, Yu Shen, etc.: Regression Analysis of Combined Incident and Prevalent Cohort. Hai Shu (presenter), Peng Wei, etc.: High-Dimensional Decomposition-Based Canonical Correlation Analysis. Jack Lee, etc.: BayesESS: An R package and a Web-based Application for Quantifying the Impact of Parametric Priors in Bayesian Analysis. Jeffrey S. Morris, etc.: Function-on-Scalar Quantile Regression with Application to Mass Spectrometry Proteomics Data. Ying Yuan, etc.: A Continuous Reassessment Method for Pediatric Phase I Clinical Trials. Jing Ning, etc.: Quantifying the Evidence of Selective Publishing in Network Meta-Analysis: An EM Algorithm-Based Approach. Suyu Liu, Peter Thall and Ying Yuan, etc.: Group Sequential Enrichment Designs Based on Adaptive Regression of Response and Survival Time on High Dimensional Covariates. Hojin Yang (speaker), Jeffrey S. Morris, etc.: Regression Analyses of Distributions using Quantile Functional Regression. Liangliang Zhang (speaker): Bayesian Variable Selection in Regression with Compositional Covariates
ENAR Posters
Yushu Shi (presenter), Liangliang Zhang, Kim-Anh Do, Robert Jenq and Christine Peterson: A Bayesian Approach for Flexible Clustering of Microbiome Data. Research Statistical Analyst Dawen Sui (presenter) and Mary Elizabeth Edgerton: Body Mass Index and Breast Cancer Survival: A Censored Quantile Regression Analysis. Fang Xia (presenter), Jing Ning, Liang Li, Xuelin Huang, etc.: A Signature Enrichment Design with Bayesian Adaptive Randomization for Cancer Clinical Trials. Yanhong Zhou (presenter), J. Jack Lee and Ying Yuan: Utility-based Seamless Phase I/II Trial Design to Identify the Optimal Biological Dose for Targeted and Immune Therapies.
MD ANDERSON BIOSTATISTICS AT JSM 2018
Faculty, analysts, postdoctoral fellows and graduate researchers from the Biostatistics department organized sessions, gave presentations, and/or had coauthored work presented at JSM 2018 in Vancouver, BC, Canada, July 28–August 2, 2018.
JSM Invited papers
Jeffrey Morris (presenter); Postdoc Fellows Hojin Yang & Michelle Miranda, et al: Bayesian regression models for big spatially or longitudinally correlated functional data. Peng Wei (presenter); GRA Yiding Ma: A versatile and adaptive multiple functional annotations-based association test of whole-genome sequencing data. Ying Yuan (presenter), et al: Bayesian phase I/II biomarker-based dose finding for precision medicine with molecularly targeted agents. Suyu Liu (presenter), Ying Yuan, et al: A Bayesian phase I/II trial design for immunotherapy. Jeffrey Morris & Min Jin Ha, et al (coauthors): Pathway and network-based integrative Bayesian modeling of multiplatform genomic data. Peter Thall & Ying Yuan, et al: former postdoc Thomas Murray (presenter): Robust treatment comparison based on utilities of semi-competing risks in non-small-cell lung cancer.
JSM Contributed papers
Xuelin Huang is the organizer and Postdoctoral Fellow Yayuan Zhu is the chair for the topic: Survival Analysis Developments for Improving Medical Decision Making — Contributed Papers Xuelin Huang (presenter), et al: Optimal timing of stem cell transplant for leukemia patients. Senior Stat Analyst Nga Nguyen (presenter); Yisheng Li: Evaluating the performance of different confidence intervals for the Bland-Altman limits of agreement for non-normal data. Jian Wang (presenter); Sanjay Shete: Assessing indirect effect in a mediation model with a censored mediator. GRA Youyi Zhang (presenter); Jeffrey Morris, et al: Bayesian integrative analysis of radiogenomics. Shouhao Zhou (presenter): Robust dose response estimation. Ying Yuan (presenter), et al: DCPAS: a Bayesian drug-combination platform design with adaptive shrinkage. Jing Ning & Xuelin Huang, et al: Efficient two-stage designs and proper inference for animal studies. Jeffrey Morris,, et al: Improved selection of high-dimensional neuroimaging biomarkers associated with neurodegenerative disease progression. Sanjay Shete, et al: Assessing current temporal and space-time anomalies of disease incidence. Donald Berry, et al: GBM AGILE: a phase II/III platform design with signature identification. Jeffrey Morris, et al: Bayesian nonparametric differential analysis with application to colorectal cancer DNA methylation. Liang Li, et al: Dynamic prediction of competing risk events using landmark sub-distribution hazard model with multivariate longitudinal biomarkers.
JSM Posters
Senior Stat Analyst Wei Qiao (presenter); Xuelin Huang & Jing Ning: Clinical trial design comparison with covariate-adjusted and response adaptive randomization. Research Stat Analyst M. Laura Rubin (presenter), et al: Effect of longitudinal intracranial pressure on ordinal Glasgow outcome scale using a joint model approach. Jeffrey Morris, Rice University GRA (presenter): Bayesian functional quantile regression. Liang Li, et al: Using stratified propensity score matching approach to adjust risk assessment for breast reconstruction patients . Nabihah Tayob, et al: Nonparametric group sequential methods for recurrent and terminal events from multiple follow-up windows.
OTHER NEWS AND HONORS
Morris Receives MD Anderson 2018-19 Distinguished Faculty Mentor Award
Jeffrey Morris, Ph.D., was selected for the 2018 MD Anderson Distinguished Faculty Mentor Award, which he received April 11. Recipients of this prestigious award, created in 2010, are nominated by no less than three separate faculty members whom they mentor within the institution.
Urbauer Joins MD Anderson Wall of Science Honorees
Diana Urbauer, Principal Statistical Analyst, and her former teammate Mark Munsell had their pictures hung on the MD Anderson Wall of Science, along with Dr. Michael Frumovitz’s team, for their role in the development and design of a pivotal Phase III trial to determine the non-inferiority of Stryker’s PINPOINT Endoscopic Fluorescence Imaging System, as compared to the current imaging system for detecting sentinel lymph nodes in women with cervical or endometrial cancer. The new technology was found to be far superior, and as a result of their collective efforts, the device received FDA approval for use in detecting sentinel lymph nodes in the patient population. The Wall of Science recognizes excellent work done by MD Anderson faculty and teams, displaying high-impact journal articles that are selected on a quarterly basis.
Ning Invited to Speak by Royal Statistical Society
Jing Ning, Ph.D. was honored with an invitation to present at the Royal Statistical Society in September. There, she will present on the topic of the semiparametric model for bivariate survival data subject to biased sampling.
Thall Invited to Speak at the OncoStat Annual Meeting and as Keynote at Annual Meeting of International Society for Clinical Biostatistics
Peter Thall, Ph.D., presented the invited half day short course, “Dysfunctional Conventions in Medical Statistics: Some Practical Alternatives,” at the OncoStat Annual meeting in Hartford, Connecticut, April 26-28, 2019. He also will present the Keynote Address at the annual meeting of the International Society for Clinical Biostatistics in Leuven, Belgium, July 14-18, 2019.
Biostatistics Student Awarded JSM 2019 Risk Analysis Section Student Paper Award, Runner UP
Wen Li, a current Ph.D. student at The University of Texas School of Public Health (supervised by Jing Ning, Ph.D.) is the recipient of the JSM 2019 Risk Analysis Section student paper award, runner up, for a paper titled: Semiparametric for Risk Assessment Under Two-phase Sampling.
Biostatistics Student Awarded JSM 2019 Section on Bayesian Statistical Science Student Award
Rice University student Yusha Liu (supervised by Jeffrey Morris, Ph.D.) won the Joint Statistical Meetings (JSM) 2019 Section on Bayesian Statistical Science (SBSS) student award for her paper on Function-on-Scalar Quantile Regression with Application to Mass Spectrometry Proteomics Data.
Lee a Keynote Speaker at BAYES 2018 Cambridge: Bayesian Biostatistics Workshop
Professor J. Jack Lee, Kenedy Foundation Chair in Cancer Research, was a keynote speaker at the Bayesian Biostatistics Workshop, held June 20-22 in Cambridge, UK. The workshop was a satellite event of the 2018 International Society for Bayesian Analysis (ISBA) World Meeting.
Ning Awarded Sabin Fellowship
Associate Professor Jing Ning was named a recipient of MD Anderson's Andrew Sabin Fellowship for the category of population and quantitative sciences.
Morris Featured in MD Anderson's Cancer Frontline: Using integromics to better understand and treat colorectal cancer
Professor Jeffrey S. Morris describes some of the collaborative work he is undertaking with members of the Colorectal Cancer Subtyping Consortium and MD Anderson's Colorectal Cancer Moon Shot.
MD Anderson Biostatistics at the ENAR 2019 Spring Meeting
Faculty, analysts, postdoctoral fellows and graduate researchers from the Biostatistics department organized sessions, gave presentations, and/or had coauthored work presented at ENAR 2019 in Philadelphia, Pennsylvania, USA, March 24-27, 2019.
ENAR Invited Sessions
Liang Li (speaker): Dynamic Prediction of Competing Risk Events using Landmark Sub-Distribution Hazard Model with Multivariate Longitudinal Biomarkers. Jeffrey S. Morris (speaker), Hojin Yang, Michelle Miranda, etc.: Bayesian Regression Models for Big Spatially or Longitudinally Correlated Functional Data. Peter F. Thall, etc.: Bayesian Variable Selection for a Semi-Competing Risks Model with Three Hazard Functions. Ying Yuan (speaker): A Bayesian Adaptive Design for Biosimilar Clinical Trials Using Calibrated Power Prior.
ENAR Contributed Sessions
Jing Ning, Yu Shen, etc.: Regression Analysis of Combined Incident and Prevalent Cohort. Hai Shu (presenter), Peng Wei, etc.: High-Dimensional Decomposition-Based Canonical Correlation Analysis. Jack Lee, etc.: BayesESS: An R package and a Web-based Application for Quantifying the Impact of Parametric Priors in Bayesian Analysis. Jeffrey S. Morris, etc.: Function-on-Scalar Quantile Regression with Application to Mass Spectrometry Proteomics Data. Ying Yuan, etc.: A Continuous Reassessment Method for Pediatric Phase I Clinical Trials. Jing Ning, etc.: Quantifying the Evidence of Selective Publishing in Network Meta-Analysis: An EM Algorithm-Based Approach. Suyu Liu, Peter Thall and Ying Yuan, etc.: Group Sequential Enrichment Designs Based on Adaptive Regression of Response and Survival Time on High Dimensional Covariates. Hojin Yang (speaker), Jeffrey S. Morris, etc.: Regression Analyses of Distributions using Quantile Functional Regression. Liangliang Zhang (speaker): Bayesian Variable Selection in Regression with Compositional Covariates
ENAR Posters
Yushu Shi (presenter), Liangliang Zhang, Kim-Anh Do, Robert Jenq and Christine Peterson: A Bayesian Approach for Flexible Clustering of Microbiome Data. Research Statistical Analyst Dawen Sui (presenter) and Mary Elizabeth Edgerton: Body Mass Index and Breast Cancer Survival: A Censored Quantile Regression Analysis. Fang Xia (presenter), Jing Ning, Liang Li, Xuelin Huang, etc.: A Signature Enrichment Design with Bayesian Adaptive Randomization for Cancer Clinical Trials. Yanhong Zhou (presenter), J. Jack Lee and Ying Yuan: Utility-based Seamless Phase I/II Trial Design to Identify the Optimal Biological Dose for Targeted and Immune Therapies.
Two biostatistics faculty are Fellows of the Society for Clinical Trials
Professors Peter F. Thall (2014) and J. Jack Lee (2017) are Fellows of the Society for Clinical Trials. This fellowship honors society members who have made significant contributions to the advancement of clinical trials and to the society.
10 biostatistics faculty are ASA fellows
Ten of the department's faculty members have attained the prestigious honor of being named a Fellow in the American Statistical Association: Donald A. Berry (1986), Kim-Anh Do (2006), Yu Shen (2007), J. Jack Lee (2008), Jeffrey S. Morris (2011), Sanjay Shete (2012), Peter F. Thall (2015), Kenneth R. Hess (2017), Xuelin Huang (2017), and Ying Yuan (2017).
Faculty Position
Assistant , Associate, or Full Professor
The Department of Biostatistics at The University of Texas MD Anderson Cancer Center is seeking candidates for multiple tenured/tenure-track faculty positions at the Assistant, Associate, or Full Professor level. The department invites applications from qualified individuals able to establish themselves as research leaders and demonstrate prowess in interdisciplinary collaborative scientific research. We are willing to consider researchers who can contribute to the development of methodology and its applications to biomedical research in various areas, but are especially interested in individuals in research areas relating to early detection and cancer screening, clinical trial design, imaging, computer-intensive methodology including machine learning, and integrative analyses of multi-platform high-dimensional data including genomic, proteomic, and microbiome data analysis. A Ph.D. in statistics, biostatistics or a related field is required.
The Department of Biostatistics has 20 faculty members and 40 masters and doctoral level research analysts and more than 12 postdoctoral fellows. Faculty members are actively involved in collaborative and methodological research in such diverse areas as clinical trial design, cancer screening and early detection, bioinformatics, genomic pathway analysis, network analysis, integrative modeling of multiple types of complex data including high-dimensional omic data, functional data analysis, Bayesian methodology, longitudinal and survival analysis, statistical genetics, population health research, and behavioral/social statistics. Faculty collaborate with cancer scientists in all cancer areas and levels of cancer research from drug discovery, preclinical studies, population-based studies, and clinical trials. This research includes work with world-class researchers, including James Allison, the 2018 Nobel Prize winner for medicine, and involves large-scale studies and programs, including the Moon Shots program, that produce large and important cancer data sets requiring quantitative input and with translational impact potential. Faculty members also have opportunities in the affiliated biostatistics doctoral programs at the University of Texas, Texas A&M University, and Rice University. The department is supported by strong resources, which includes an active quantitative research computing team with specialties in database design, web-based clinical trial support, scientific programming, and software engineering. Information about the department and programs offered can be found at http://www3.mdanderson.org/depts/biostatistics/. Further questions regarding the position may be directed to one of the co-chairs on the selection committee: Jeffrey Morris (jefmorris@mdanderson.org), Yu Shen (yshen@mdanderson.org), or Ying Yuan (yyuan@mdanderson.org) with the subject line “faculty position 2019” in the email.
MD Anderson Cancer Center offers competitive salaries and an outstanding personal and professional benefits package. Houston is one of the world’s most innovative and diverse cities, nurturing great neighborhoods, competitive private and public schools, an exceptional music and theater scene, highly acclaimed museums, international cuisine, and year-round outdoor recreational activities.
MD Anderson Cancer Center is an equal opportunity employer and does not discriminate on the basis of race, color, national origin, gender, sexual orientation, age, religion, disability or veteran status, except where such distinction is required by law. All positions at The University of Texas MD Anderson Cancer Center are security sensitive and subject to examination of criminal history record information. MD Anderson Cancer Center is a smoke-free and drug-free environment.
Consideration of applications will continue until the position is filled. Interested applicants should email (or mail) a cover letter outlining the relevance of their research experience and interests to the position description, a curriculum vitae, a brief statement of current and proposed research plan, and 3 letters of recommendation to:
Faculty Search Committee
Department of Biostatistics
The University of Texas MD Anderson Cancer Center
P.O. Box 301402
Houston, TX 77230-1402
Email: biostat-search@mdanderson.org
Statistical Analyst Position
Successful candidates will join a team of biostatisticians working on a wide variety of collaborative projects in cancer research. The University of Texas MD Anderson Cancer Center supports and promotes professional growth and mentoring, as well as continuing education, creativity, and discovery.
Responsibilities
Collaborate with clinicians and scientists to plan meaningful studies, statistically analyze and communicate/document the results:
- Assess relevant literature and existing data
- Perform simulations and complex statistical analyses using advanced statistical methods and programming
- Prepare statistical considerations for clinical trial designs or grant applications
- Perform biostatistical reviews of research protocols
- Collaborate on development of new statistical methodology
- Prepare written reports, including reports of data for committee and scientific meetings
- Collaborate with investigators on manuscripts
- Make original contributions to research projects
- Take initiative in professional activities
- If hired as or promoted to a senior position, participate in training and supervising junior statistical analysts
To be considered, send a letter of interest, curriculum vitae and three (3) letters of reference (include contact information for references) to dqs-stat-job@mdanderson.org
Minimum Qualifications:
- Master's degree in biostatistics, bioinformatics, statistics, computing, or related field
- Working knowledge of Windows and/or UNIX operating systems
- Experience in statistical programming and analysis
- Excellent oral and written communication skills in English
- Experience with mainframe and/or PC databases, document processing and statistical software such as SAS and S-Plus
Desired Qualifications:
- Experience writing reports and analytical sections of grant applications
- Extensive experience in statistical consulting, data analysis, design and management of clinical trials in the biomedical or cancer research setting
Salary: Competitive; commensurate with experience
EEO & Employment Eligibility
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, sexual orientation, gender identity/expression, disability, veteran status, genetic information or any other basis protected by MD Anderson policy or by federal, state or local laws, unless such distinction is required by law. All positions at MD Anderson Cancer Center are security sensitive and subject to examination of criminal history record information. MD Anderson Cancer Center provides a smoke-free and drug-free environment.
Postdoctoral Fellow Position
Position with Jeffrey S. Morris, Ph.D.
Area: Computational statistics with applications in biostatistics and bioinformatics
Duties & Responsibilities: The research will involve developing novel statistical and computational methodology for the analysis of functional and imaging data, with a special focus on complex, high-dimensional functions and images. One project of interest is Bayesian methods for LC/MS proteomic data, combining biological knowledge and functional data modeling techniques using fast approximate Bayesian computational procedures. Other application-driven methodological research may also be undertaken, with other application areas including event-related potentials (ERP), diffusion MRI methods such as DTI/MAP-MRI, functional data on the sphere and multivariate real-time time series from glaucoma studies, and various types of genomic data that can be modeled in an integrated fashion with corresponding clinical outcome data collected from large numbers of patients with colon cancer. The genomic data may include copy number alterations, methylation, miRNA, ncRNA, microarray, RNAseq, and proteomic data. We have a working group carrying out deep characterization of newly established molecular subtypes of colon cancer (Guinney et al. 2015, Nature Medicine), which involves many potential projects in data integration that we hope will lead to new strategies in precision therapy.
Qualifications: We seek a highly motivated individual with a Ph.D. in statistics/biostatistics or related quantitative fields. Must have strong methodologic training in statistics/biostatistics; strong programming skills, in particular R/Matlab, and possibly one lower-level computer language such as C or Fortran; and interest in statistical methodology research. Interest or background in neuroimaging, bioinformatics, genomics, or proteomics is a plus. Expertise or skills in any of the following areas is desirable: analysis of high-dimensional data, Bayesian MCMC computations, approximate Bayesian computational methods, variable selection and sparsity priors, linear models, nonparametric regression, spatio-temporal data, multivariate techniques, functional data analysis, and image data analysis.
Application: Send a cover letter, CV, and research statement (with three references and their contact information) to:
pcunning@mdanderson.org
and
jefmorris@mdanderson.org
Subject line: Morris postdoc
Application deadline: Consideration of applications will begin immediately, and continue until the positions are filled.
Salary: $65,000 USD/year
EEO & Employment Eligibility: It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, sexual orientation, gender identity/expression, disability, veteran status, genetic information or any other basis protected by MD Anderson policy or by federal, state or local laws, unless such discrimination is required by law. All positions at MD Anderson Cancer Center are security sensitive and subject to examination of criminal history record information. MD Anderson Cancer Center provides a smoke-free and drug-free environment.