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MotifModeler - Yunlong Liu Lab

Welcome to MotifModeler homepage.

MotifModeler is a tool that aims at identifying functional binding sites from array-derived gene expression data.  This approach has several unique features.  First, it incorporates combinatorial effects of binding sites of different transcription factors. Second, in addition to identification of binding sites, MotifModeler estimates functional effects (stimulatory or inhibitory roles on gene expression) of predicted motifs under the conditions compared. Third, the prediction is based on mRNA expression levels under contrasting conditions, e.g., presence or absence of drug, so that it finds sequence motifs relevant to particular biological effects rather than just finding consensus motifs across multiple species.  We have applied this approach to several biological systems, such as interferon stimulation on peripheral blood monocytes [1], anabolic responses in bone cells through mechanical loading and administration of bone morphogenic proteins (BMPs) [2], regulatory mechanisms responsible for fetal alcohol syndrome [3], and androgen dependency in prostate cancer [4]. Through these applications, MotifModeler demonstrated significant advantages in identifying transcriptional mechanisms in complex biological systems.

We have further we expanded this algorithm by enabling identification of functional microRNAs that are responsible to the global gene expression changes under certain biological conditions [3,4]. Using array-derived gene expression data, this algorithm is very useful in raising testable hypotheses for putative microRNA functions.

Access MotifModeler online service. 

  • Initiate a job.  (The input should be a .csv file that contains all the differentially expressed genes).  There are two columns in the file, Entrez gene ID, and fold change.  Currently, only Entrez gene ID is accepted.  A sample file can be downloaded: MM-samples.csv.  To retrieve Entrez gene IDs from other identifiers, please refer to the ID lookup tables for human, mouse, and rat. The last column in this list is the Entrez gene ID.
  • Retrieve/check status of your job. (sample job id: Q10qgiY2)



[1] Liu Y., Taylor M.W., Edenberg H.J.: Model-based identification of cis-acting elements from microarray data. Genomics 2006, 88(4):452-461.
[2] Hamamura K., Liu Y., and Yokota H. Microarray Analysis of Thapsigargin-Induced Stress to Endoplasmic Reticulum of Mouse Osteoblasts, Journal of Bone and Mineral Metabolism 2008;26(3):231-40. Epub 2008 May 11.
[3] Wang, G., Wang, X., Li, L., Nephew, N.P., Edenberg, H.J., Zhou, F.C., Liu, Y., Identification of Transcription Factor and microRNA Binding Sites in response to fetal alcohol syndrome, BMC Genomics 2008, 9 (S1):S19
[4] Wang, G., Wang, Y., Feng, W., Wang, X., Yang, J.Y., Zhao, Y, Wang, Y., Liu, Y., Transcription factor and microRNA regulatio
n in androgen-dependent and -independent prostate cancer cells, BMC Genomics 2008, 9 (S2):S22.