Marcela K. Sjöberg-Herrera

The paper develops methods to model transcription factor binding in modified DNA by expanding the DNA alphabet and adapting existing tools to handle custom alphabets, identifying modification-sensitive motifs and validating them with experimental data.

The paper benchmarks isoform quantification tools on simulated single-cell RNA-seq data, finding good performance on SMARTer and SMART-seq2 but poor on Drop-seq, and highlights biological insights from real data.

The paper presents full-length de novo genome assemblies for 16 inbred mouse strains, identifying strain-specific haplotypes and novel functional loci, including a large unannotated gene with potential developmental roles.