Arttu Jolma

The paper benchmarks methods for inferring transcription factor binding specificities using a large community challenge and finds deep learning models outperform traditional methods, though positional weight matrices are competitive.

This study identifies DNA binding motifs for 98 human transcription factors using meSMiLE-seq, revealing methylation-sensitive binding preferences for some TFs.

The paper uses GHT-SELEX to show many human TFs have high intrinsic sequence specificity and complex DNA binding, often matching in vivo ChIP-seq results.

The paper evaluates cross-platform DNA motif discovery tools using 4,237 experiments to identify reliable transcription factor binding motifs and highlights challenges in motif detection.

The paper identifies genomic binding sites of 166 poorly characterized human transcription factors, revealing that some bind to dark matter DNA and others to regulatory regions.

The paper systematically determines the sequence specificity of 332 poorly characterized human transcription factors, identifying over 4,000 experiments and revealing tens of thousands of new TF binding sites.

The paper curates a comprehensive catalogue of human DNA-binding transcription factors using Gene Ontology definitions and provides access to it via an online resource.

The paper identifies binding specificities of human RNA-binding proteins using HTR-SELEX, revealing that 70% bind linear sequences and 30% bind structured motifs, with novel roles for ZC3H12A/B/C in viral transcript degradation.

The paper introduces ATI, a method to measure TF DNA-binding activity, and finds that few TFs with strong binding activity determine open chromatin.