• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 39 matches

• 2017
• 
  Marco Albrecht, Damian Stichel, Benedikt Müller, Ruth Merkle, Carsten Sticht, Norbert Gretz, Ursula Klingmüller, Kai Breuhahn, Franziska Matthäus:
  TTCA: an R package for the identification of differentially expressed genes in time course microarray data. BMC Bioinform. 18(1): 33:1-33:11 (2017)
• 
  Qihua Tan, Mads Thomassen, Mark Burton, Kristian Fredløv Mose, Klaus Ejner Andersen, Jacob v. B. Hjelmborg, Torben Arvid Kruse:
  Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data. J. Integr. Bioinform. 14(2) (2017)
• 
  Li Zhang, H. C. Wu, S. C. Chan, Chong Wang:
  Dynamic gene and transcriptional regulatory networks inferring with multi-Laplacian prior from time-course gene microarray data. DSP 2017: 1-5
• 
  Li Zhang, H. C. Wu, Jian-Qiang Lin, S. C. Chan:
  Dynamic gene regulatory network analysis using Saccharomyces cerevisiae large-scale time-course microarray data. ISCAS 2017: 1-4
• 2015
• 
  Shing-Chow Chan, Li Zhang, Ho-Chun Wu, Kai Man Tsui:
  A Maximum A Posteriori Probability and Time-Varying Approach for Inferring Gene Regulatory Networks from Time Course Gene Microarray Data. IEEE ACM Trans. Comput. Biol. Bioinform. 12(1): 123-135 (2015)
• 
  Li Zhang, H. C. Wu, Shing-Chow Chan:
  Large-scale dynamic gene regulatory networks analysis for time course DNA microarray data from C. elegans, preliminary results and findings. DSP 2015: 552-556
• 2013
• 
  Hyung-Seok Choi, Youngchul Kim, Kwang-Hyun Cho, Taesung Park:
  Integrative analysis of time course microarray data and DNA sequence data via log-linear models for identifying dynamic transcriptional regulatory networks. Int. J. Data Min. Bioinform. 7(1): 38-57 (2013)
• 2012
• 
  Ola ElBakry, M. Omair Ahmad, M. N. S. Swamy:
  Identification of Differentially Expressed Genes for Time-Course Microarray Data Based on Modified RM ANOVA. IEEE ACM Trans. Comput. Biol. Bioinform. 9(2): 451-466 (2012)
• 2011
• 
  Qihua Tan, Mads Thomassen, Jacob v. B. Hjelmborg, Anders Clemmensen, Klaus Ejner Andersen, Thomas K. Petersen, Matthew McGue, Kaare Christensen, Torben Arvid Kruse:
  A Growth Curve Model with Fractional Polynomials for Analysing Incomplete Time-Course Data in Microarray Gene Expression Studies. Adv. Bioinformatics 2011: 261514:1-261514:6 (2011)
• 
  Valéria Lima Passos, Frans E. S. Tan, Martijn P. F. Berger:
  Cost-efficiency considerations in the choice of a microarray platform for time course experimental designs. Comput. Stat. Data Anal. 55(1): 944-954 (2011)
• 
  Lingyan Ruan, Ming Yuan:
  Statistical Analysis of Time Course Microarray Data. Handbook of Statistical Bioinformatics 2011: 299-313
• 2010
• 
  Paul Craig, Alan Cannon, Jessie B. Kennedy, Robert Kukla:
  Pattern Browsing and Query Adjustment for the Exploratory Analysis and Cooperative Visualisation of Microarray Time-Course Data. CDVE 2010: 199-206
• 2009
• 
  Ryosuke R. Ishiwata, Masaki S. Morioka, Soichi Ogishima, Hiroshi Tanaka:
  BioCichlid: central dogma-based 3D visualization system of time-course microarray data on a hierarchical biological network. Bioinform. 25(4): 543-544 (2009)
• 
  Martin J. Aryee, José A. Gutiérrez-Pabello, Igor Kramnik, Tapabrata Maiti, John Quackenbush:
  An improved empirical bayes approach to estimating differential gene expression in microarray time-course data: BETR (Bayesian Estimation of Temporal Regulation). BMC Bioinform. 10: 409 (2009)
• 
  Stephen C. Billups, Margaret C. Neville, Michael Rudolph, Weston Porter, Pepper Schedin:
  Identifying significant temporal variation in time course microarray data without replicates. BMC Bioinform. 10 (2009)
• 
  María José Nueda, Patricia Sebastián, Sonia Tarazona, Francisco García-García, Joaquín Dopazo, Alberto Ferrer, Ana Conesa:
  Functional assessment of time course microarray data. BMC Bioinform. 10(S-6) (2009)
• 
  Claudia Angelini, Daniela De Canditiis, Marianna Pensky:
  Bayesian models for two-sample time-course microarray experiments. Comput. Stat. Data Anal. 53(5): 1547-1565 (2009)
• 
  Sung-Gon Yi, Yoon-Jeong Joo, Taesung Park:
  Rank-Based Clustering Analysis for the Time-Course microarray Data. J. Bioinform. Comput. Biol. 7(1): 75-91 (2009)
• 
  Yushi Liu, Joseph S. Verducci, Irvin R. Schultz, Sharon Hook, James J. Nagler, Gheorghe Craciun, Kaitlin Sundling, William L. Hayton:
  Time course analysis of microarray data for the pathway of reproductive development in female rainbow trout. Stat. Anal. Data Min. 2(3): 192-208 (2009)
• 2008
• 
  Sudhakar Jonnalagadda, Rajagopalan Srinivasan:
  Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data. BMC Bioinform. 9 (2008)
• 
  Guei-Feng Tsai, Annie Qu:
  Testing the significance of cell-cycle patterns in time-course microarray data using nonparametric quadratic inference functions. Comput. Stat. Data Anal. 52(3): 1387-1398 (2008)
• 
  Kevin McCormick, Roli Shrivastava, Li Liao:
  SlopeMiner: An Improved Method for Mining Subtle Signals in Time Course Microarray Data. FAW 2008: 28-34
• 
  Theresa Scharl, Friedrich Leisch:
  Quality-Based Clustering of Functional Data: Applications to Time Course Microarray Data. GfKl 2008: 675-684
• 
  Adam Zagdanski, Rafal Kustra:
  Exploration of High-Dimensional Time Series Using Regularized Reduced Rank Approach: Application in Time-Course Microarray. IADIS European Conf. Data Mining 2008: 129-133
• 2007
• 
  Lifeng Wang, Guang Chen, Hongzhe Li:
  Group SCAD regression analysis for microarray time course gene expression data. Bioinform. 23(12): 1486-1494 (2007)
• 
  Jihoon Kim, Ju Han Kim:
  Difference-based clustering of short time-course microarray data with replicates. BMC Bioinform. 8 (2007)
• 
  Reuben Thomas, Carlos J. Paredes, Sanjay Mehrotra, Vassily Hatzimanikatis, Eleftherios T. Papoutsakis:
  A model-based optimization framework for the inference of regulatory interactions using time-course DNA microarray expression data. BMC Bioinform. 8 (2007)
• 
  Juntao Li, Jianhua Liu, Karuturi R. Krishna Murthy:
  Data-Driven Smoothness Enhanced Variance Ratio Test to Unearth Responsive Genes in 0-Time Normalized Time-Course Microarray Data. ISBRA 2007: 25-36
• 2006
• 
  Kazumi Hakamada, Masahiro Okamoto, Taizo Hanai:
  Novel technique for preprocessing high dimensional time-course data from DNA microarray: mathematical model-based clustering. Bioinform. 22(7): 843-848 (2006)
• 
  Peter D. Wentzell, Tobias K. Karakach, Sushmita Roy, M. Juanita Martinez, Christopher P. Allen, Margaret Werner-Washburne:
  Multivariate curve resolution of time course microarray data. BMC Bioinform. 7: 343 (2006)

skipping 9 more matches