Simon Rasmussen
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View article: Supplementary Data 2 from Childhood Cancer Predisposition and Evolutionary Constraints: Novel Lessons from Germline Genomes from 1,127 Children with Cancer
Supplementary Data 2 from Childhood Cancer Predisposition and Evolutionary Constraints: Novel Lessons from Germline Genomes from 1,127 Children with Cancer Open
Supplementary Dataset combined
View article: Supplementary Data 1 from Childhood Cancer Predisposition and Evolutionary Constraints: Novel Lessons from Germline Genomes from 1,127 Children with Cancer
Supplementary Data 1 from Childhood Cancer Predisposition and Evolutionary Constraints: Novel Lessons from Germline Genomes from 1,127 Children with Cancer Open
Supplementery Results and Methods
View article: Data from Childhood Cancer Predisposition and Evolutionary Constraints: Novel Lessons from Germline Genomes from 1,127 Children with Cancer
Data from Childhood Cancer Predisposition and Evolutionary Constraints: Novel Lessons from Germline Genomes from 1,127 Children with Cancer Open
Purpose:Cancer predisposition syndromes (CPS) with pediatric onset are the leading known cause of childhood malignancies and are increasingly guiding clinical strategies in pediatric oncology. CPS are placed under evolutionary negative sel…
View article: Unsupervised learning of multi-omics data enables disease risk prediction in the UK Biobank
Unsupervised learning of multi-omics data enables disease risk prediction in the UK Biobank Open
Summary The size and complexity of biomedical datasets continue to grow, driving the development of methods that reduce dimensionality while preserving biological signals. Yet, when deep learning is applied to such data, the impact of prep…
View article: Predicting Olanzapine Induced BMI increase using Machine Learning on population-based Electronic Health Records
Predicting Olanzapine Induced BMI increase using Machine Learning on population-based Electronic Health Records Open
Background Weight gain is a common side effect in patients treated with olanzapine (N05AH03), contributing to increased risks of metabolic complications such as diabetes, cardiovascular disease, and reduced treatment adherence. However, pe…
View article: On the use of variational autoencoders for biomedical data integration
On the use of variational autoencoders for biomedical data integration Open
Summary Variational Autoencoders (VAEs) are a widely used framework to integrate diverse biomedical data modalities, create representations that capture the underlying structure of the datasets, and obtain insights about the relations betw…
View article: Body Fluid Proteomic Landscape of Acute Exercise
Body Fluid Proteomic Landscape of Acute Exercise Open
Physical activity improves health, yet the molecular mechanisms remain partially understood. This study presents a high-resolution, time-resolved atlas profiling 10,127 proteins across plasma, saliva, and urine from healthy adults post-acu…
View article: Personalized molecular signatures of insulin resistance and type 2 diabetes
Personalized molecular signatures of insulin resistance and type 2 diabetes Open
Insulin resistance is a hallmark of type 2 diabetes, which is a highly heterogeneous disease with diverse pathology. Understanding the molecular signatures of insulin resistance and its association with individual phenotypic traits is cruc…
View article: Tracing the evolutionary history of the CCR5delta32 deletion via ancient and modern genomes
Tracing the evolutionary history of the CCR5delta32 deletion via ancient and modern genomes Open
The chemokine receptor variant CCR5delta32 is linked to HIV-1 resistance and other conditions. Its evolutionary history and allele frequency (10%-16%) in European populations have been extensively debated. We provide a detailed perspective…
View article: Deep learning-based polygenic scores enhance generalizability of psychiatric disorders prediction
Deep learning-based polygenic scores enhance generalizability of psychiatric disorders prediction Open
Polygenic scores (PGSs) have emerged as promising tools for predicting complex traits from genetic data, however, their predictive performance for psychiatric disorders remains limited and the added value of deep learning (DL) over linear …
View article: DoBSeqWF: A framework for sensitive detection of individual genetic variation in pooled sequencing data
DoBSeqWF: A framework for sensitive detection of individual genetic variation in pooled sequencing data Open
Motivation Population screening for rare genetic diseases is limited by the high cost of next- generation sequencing. Double-batched sequencing (DoBSeq) is a cost-effective method for assigning rare variants to individuals using two-dimens…
View article: Obesity- and age-dependent genetic regulation of the plasma proteome in children and adolescents
Obesity- and age-dependent genetic regulation of the plasma proteome in children and adolescents Open
The genetic regulation of the plasma proteome has been extensively studied in adult populations, yet protein quantitative trait loci (pQTL) studies in children and adolescents remain largely unexplored. Here, we mapped pQTLs for 178 plasma…
View article: Evaluating large language models for predicting psychiatric acute readmissions from clinical notes of population-based EHR
Evaluating large language models for predicting psychiatric acute readmissions from clinical notes of population-based EHR Open
Psychiatric patients often have complex symptoms and anamneses recorded as unstructured clinical notes. Large language models (LLM) now enable large-scale utilization of text data; however, there is a current lack of LLMs specialized for p…
View article: EIRsurvival: Deep Learning-based time-to-event analysis on high-dimensional genotype and multi-omics data
EIRsurvival: Deep Learning-based time-to-event analysis on high-dimensional genotype and multi-omics data Open
Motivation: Time-to-event data in disease occurrence is often right-censored, requiring survival models for accurate predictions. While deep learning advancements have extended traditional Cox models, current approaches do not allow modeli…
View article: Accurate plasmid reconstruction from metagenomics data using assembly-alignment graphs and contrastive learning
Accurate plasmid reconstruction from metagenomics data using assembly-alignment graphs and contrastive learning Open
Plasmids are extrachromosomal DNA molecules that enable horizontal gene transfer in bacteria, often conferring advantages such as antibiotic resistance. Despite their significance, plasmids are underrepresented in genomic databases due to …
View article: Plasma proteome variation and its genetic determinants in children and adolescents
Plasma proteome variation and its genetic determinants in children and adolescents Open
View article: Leveraging haplotype information in heritability estimation and polygenic prediction
Leveraging haplotype information in heritability estimation and polygenic prediction Open
Polygenic prediction has yet to make a major clinical breakthrough in precision medicine and psychiatry, where the application of polygenic risk scores is expected to improve clinical decision-making. Most widely used approaches for estima…
View article: Gut heavy metal and antibiotic resistome of humans living in the high Arctic
Gut heavy metal and antibiotic resistome of humans living in the high Arctic Open
Contaminants, such as heavy metals (HMs), accumulate in the Arctic environment and the food web. The diet of the Indigenous Peoples of North Greenland includes locally sourced foods that are central to their nutritional, cultural, and soci…
View article: Binning meets taxonomy: TaxVAMB improves metagenome binning using bi-modal variational autoencoder
Binning meets taxonomy: TaxVAMB improves metagenome binning using bi-modal variational autoencoder Open
A common procedure for studying the microbiome is binning the sequenced contigs into metagenome-assembled genomes. Currently, unsupervised and self-supervised deep learning based methods using co-abundance and sequence based motifs such as…
View article: Taxometer: Improving taxonomic classification of metagenomics contigs
Taxometer: Improving taxonomic classification of metagenomics contigs Open
For taxonomy based classification of metagenomics assembled contigs, current methods use sequence similarity to identify their most likely taxonomy. However, in the related field of metagenomic binning, contigs are routinely clustered usin…
View article: An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomes
An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomes Open
Introduction Postoperative complications affect up to 15% of surgical patients constituting a major part of the overall disease burden in a modern healthcare system. While several surgical risk calculators have been developed, none have so…
View article: Non-linear genetic regulation of the blood plasma proteome
Non-linear genetic regulation of the blood plasma proteome Open
Although thousands of genetic variants are linked to human traits and diseases, the underlying mechanisms influencing these traits remain largely unexplored. One important aspect is to understand how proteins are regulated by the genome by…
View article: Imputation of label-free quantitative mass spectrometry-based proteomics data using self-supervised deep learning
Imputation of label-free quantitative mass spectrometry-based proteomics data using self-supervised deep learning Open
View article: Modeling nascent transcription from chromatin landscape and structure
Modeling nascent transcription from chromatin landscape and structure Open
Different cell types and their associated functionalities emerge from a single genomic sequence when certain regions are expressed while others remain silenced. Modeling gene expression and its potential malfunctioning in different cellula…
View article: BinBencher: Fast, flexible and meaningful benchmarking suite for metagenomic binning
BinBencher: Fast, flexible and meaningful benchmarking suite for metagenomic binning Open
New methods for metagenomic binning are typically evaluated using benchmarking software, and become tuned to maximize whatever criterion is measured by the benchmark. Subtleties in benchmarking procedures can cause misleading evaluations, …
View article: Leveraging haplotype information in heritability estimation and polygenic prediction
Leveraging haplotype information in heritability estimation and polygenic prediction Open
Polygenic prediction has yet to make a major clinical breakthrough in precision medicine and psychiatry, where the application of polygenic risk scores are expected to improve clinical decision-making. Most widely used approaches for estim…
View article: The evolutionary impact of childhood cancer on the human gene pool
The evolutionary impact of childhood cancer on the human gene pool Open
View article: Mass spectrometry-based proteomics data from thousands of HeLa control samples
Mass spectrometry-based proteomics data from thousands of HeLa control samples Open
View article: An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomes
An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomes Open
Introduction Postoperative complications affect up to 15% of surgical patients constituting a major part of the overall disease burden in a modern healthcare system. While several surgical risk calculators have been developed, none have so…
View article: 100 ancient genomes show repeated population turnovers in Neolithic Denmark
100 ancient genomes show repeated population turnovers in Neolithic Denmark Open