Eivind Valen

The paper shows EWSR1::FLI1 fusion drives the production of cancer-specific neoproteins in Ewing sarcoma, revealing a reversible dark proteome with therapeutic potential.

The paper uses ribosome profiling to study translation changes in synaptoneurosomes from rat cortical tissue after group 1 mGluR activation, showing increased translation of synaptic and ribosomal protein mRNAs.

The paper defines an extended translation initiation sequence (eTIS) and shows that a deep-learning model trained on eTIS features accurately predicts translation initiation, revealing that the Kozak sequence is not optimal and identifying conserved nucleotides that enhance initiation efficiency.

The paper identifies 25% of 7,264 non-canonical open reading frames (ncORFs) as producing translated gene products, supported by over 3,000 peptides from 3.8 billion mass spectra.

This study uses RCP-seq to analyze translation initiation dynamics in mouse brain tissues, revealing SSU poising and uORF effects on translational efficiency.

This paper presents a T cell gene correction pipeline using CRISPR/Cas9 and HDR to correct monogenic mutations in IEI models, achieving up to 80% bi-allelic editing with no detectable off-target effects.

The paper introduces Nano3P-seq, a nanopore-based method to analyze RNA polyA tail composition and length at single-molecule resolution, along with software PolyTailor for accurate estimation of transcript abundances and tail dynamics.

The paper expands and refines a reference catalog of human non-canonical open reading frames (ncORFs) by incorporating more datasets and introducing a translation signature score framework to prioritize high-quality ncORFs.

CHOPOFF improves CRISPR off-target detection by addressing limitations in symbolic alignments and introducing efficient data structures for accurate and fast prediction.

This study identifies the IRE-1/XBP-1 pathway as critical for cold-induced gene regulation in C. elegans, linking it to survival during cold stress.

This paper introduces Ribosome Decision Graphs (RDGs) to represent eukaryotic RNA translation complexity, enabling analysis of translation patterns and genetic variation effects.

Nano3P-seq quantifies RNA abundance, tail composition, and tail length dynamics at single-read resolution without PCR or adapters.

The paper introduces SMS-seq, a method to analyze RNA structure at the single-molecule level, revealing structural dependencies, breathing, and ensembles.

The paper evaluates DNA repair protein-Cas9 fusions for improving CRISPR editing efficiency, finding that most require optimization for specific cell types and genomic loci.

This study uses reciprocal zebrafish-medaka hybrids to show that maternal factors primarily control the timing of zygotic genome activation.

ORFik is an R/Bioconductor toolkit for analyzing translation data, supporting multiple high-throughput assays and providing over 30 translation-related metrics.

The paper identifies conserved ribosome stall sites across multiple species using ribosome profiling data, finding that specific amino acids facilitate stalling in RNA processing genes.

The paper shows that maternal transcription factors Pou5f3, Sox19b, and Nanog open chromatin and prime genes for activity during zygotic genome activation in zebrafish.

The paper shows that trans-splicing of mRNAs links gene transcription to translational control regulated by mTOR in Oikopleura dioica.

The paper characterizes the transcriptome-wide dynamics of translation initiation stages in a higher eukaryote and identifies regulators at each step.

tailfindr estimates poly(A) tail length from Oxford Nanopore long-read sequencing data without alignment, enabling poly(A) analysis in RNA and DNA sequencing.

ampliCan provides precise quantification and visualization of genome editing events, outperforming existing tools in benchmark tests.

Shoelaces automates ribosome profiling data processing and visualization, improving reproducibility by standardizing steps and reducing data loss in manual analysis.

The paper develops a model to identify bacterial translation initiation sites using ribosome profiling data and N-terminal proteomics, revealing novel genes and re-annotating existing ones.