activity
20052026
most citedSimulation from endpoint-conditioned, continuous-time Markov chains on a finite state space, with applications to molecular evolution

68 citations · 81 across the 12 of their papers we have counts for

collaborators

14 papers

q-bio.PE2026

Integrating opportunities and parametrized signatures for improved mutational processes estimation in extended sequence contexts

Ragnhild Laursen, Marta Pelizzola, Lasse Maretty +1

Mutational signatures describe the pattern of mutations over the different mutation types. Each mutation type is determined by a base substitution and the flanking nucleotides to t…

stat.CO2026

Markov embedding of ranked unlabelled evolutionary trees and its applications

Lasse Thorup Fallesen, Simon Pauli, Elisabeth Sommer James +2

Rooted bifurcating trees are mathematical objects used to model evolutionary relationships and arise naturally in both coalescent theory and phylogenetics. Recent numerical represe…

cs.LG2026

MM-algorithms for traditional and convex NMF with Tweedie and Negative Binomial cost functions and empirical evaluation

Elisabeth Sommer James, Asger Hobolth, Marta Pelizzola

Non-negative matrix factorisation (NMF) is a widely used tool for unsupervised learning and feature extraction, with applications ranging from genomics to text analysis and signal…

stat.ML2025★ 1 cited

Advanced posterior analyses of hidden Markov models: finite Markov chain imbedding and hybrid decoding

Zenia Elise Damgaard Bæk, Moisès Coll Macià, Laurits Skov +1

Two major tasks in applications of hidden Markov models are to (i) compute distributions of summary statistics of the hidden state sequence, and (ii) decode the hidden state sequen…

stat.AP2024

On the Relation Between Autoencoders and Non-negative Matrix Factorization, and Their Application for Mutational Signature Extraction

Ida Egendal, Rasmus Froberg Brøndum, Marta Pelizzola +2

The aim of this study is to provide a foundation to understand the relationship between non-negative matrix factorization (NMF) and non-negative autoencoders enabling proper interp…

stat.AP2022

A flexible model-based framework for robust estimation of mutational signatures

Ragnhild Laursen, Lasse Maretty, Asger Hobolth

Somatic mutations in cancer can be viewed as a mixture distribution of several mutational signatures, which can be inferred using non-negative matrix factorization (NMF). Mutationa…