Author

Georg Tremmel

Institute of Medical Science, The University of TokyoORCID 0000-0001-5706-8442Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:variant calling· 2 Research Focus:cancer & tumor microenvironment· 1 Approach:deep learning· 1 Organism:human· 1 Assay:long-read sequencing· 1 Approach:simulation· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Satoru MiyanoiD· 3 shared Seiya ImotoiD· 2 shared Arda Akdemir· 1 shared Atsushi NiidaiD· 1 shared Koshi Mimori· 1 shared Matthew Stephens· 1 shared Rui YamaguchiiD· 1 shared Ryutaro Uchi· 1 shared

Activity by Year

2015-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersBioinformatics

Satoru MiyanoORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJul 8, 2019

Nanopore base-calling from a perspective of instance segmentation

Yaozhong Zhang, Arda Akdemir, Georg Tremmel…·Rui Yamaguchi

This paper introduces a base-calling method for nanopore sequencing by framing it as a one-dimensional segmentation task, achieving competitive accuracy compared to existing methods.

6 citations

long-read sequencingdeep learning

𝕏 PostBluesky

BioinformaticsPLOS GeneticsPeer-reviewedDec 2, 2015

A simple model-based approach to inferring and visualizing cancer mutation signatures

Yuichi Shiraishi, Georg Tremmel, Satoru Miyano, Matthew Stephens

This paper introduces a simplified model-based approach for inferring and visualizing cancer mutation signatures, showing improved robustness and interpretability.

DOI 10.1371/journal.pgen.1005657

humanwhole-genome sequencing

𝕏 PostBluesky

Cancer BiologybioRxivPreprintOct 14, 2015

Cancer evolution simulation identifies possible principles underlying intratumor heterogeneity

Atsushi Niida, Satoshi Ito, Georg Tremmel…·Satoru Miyano

The paper uses a computational model to identify principles of intratumor heterogeneity in cancer evolution.

DOI 10.1101/022806

simulationcancer & tumor microenvironment

𝕏 PostBluesky