Projects: Difference between revisions

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* [[Dimont]]: general approach for discriminative de-novo motif discovery from high-throughput data
* [[Dimont]]: general approach for discriminative de-novo motif discovery from high-throughput data
* [[AUC-PR]]: area under ROC and PR curves for weighted and unweighted data
* [[AUC-PR]]: area under ROC and PR curves for weighted and unweighted data
* [[Slim]]: Sparse local inhomogenous mixture (Slim) models and dependency logos

Revision as of 17:22, 5 July 2015

This site contains projects that use Jstacs.

  • MotifAdjuster: a tool for computational reassessment of transcription factor binding site annotations
  • Prior: apples and oranges: avoiding different priors in Bayesian DNA sequence analysis
  • GenDisMix: unifying generative and discriminative learning principles
  • Dispom: de-novo discovery of differentially abundant transcription factor binding sites including their positional preference
  • MiMB: probabilistic approaches to transcription factor binding site prediction
  • SHMM: utilizing gene-pair orientations for improved analysis of ChIP-chip promoter array data
  • DSHMM: exploiting prior knowledge and gene distances in the analysis of tumor expression profiles
  • PHHMM: improved analysis of Array-CGH data
  • MeDIP-HMM: HMM-based analysis of DNA methylation profiles
  • ARHMM: integrating local chromosomal dependencies into the analysis of tumor expression profiles
  • FlowCap: molecular classification of acute myeloid leukaemia (AML) using flow cytometry data
  • TALgetter: prediction of TAL effector target sites
  • TALENoffer: genome-wide TALEN off-target prediction
  • Dimont: general approach for discriminative de-novo motif discovery from high-throughput data
  • AUC-PR: area under ROC and PR curves for weighted and unweighted data
  • Slim: Sparse local inhomogenous mixture (Slim) models and dependency logos