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Publishes scientific papers and review articles on new developments in bioinformatics and computational biology. Shorter papers report biologically interesting discoveries using computational methods and explore their applications.
Journal
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Bioinformatics Advances is a fully open access journal published by OUP and the International Society for Computational Biology. The journal publishes original research articles, reviews, application notes, opinion, perspective and Society features.
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ACCEPTED MANUSCRIPT
Yifan Dai and others
Published: 26 April 2025
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Tong Zhang and others
Published: 26 April 2025
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Xiaoyuan He and Yang Song
Bioinformatics Advances, vbaf076, https://doi.org/10.1093/bioadv/vbaf076
Published: 26 April 2025
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Chunhui Gu and others
Bioinformatics Advances, vbaf095, https://doi.org/10.1093/bioadv/vbaf095
Published: 26 April 2025
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Keun Hong Son and Je-Yoel Cho
Published: 25 April 2025
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Alison Kyrouz and others
Published: 25 April 2025
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David Gerardus Pieter van IJzendoorn and others
Published: 25 April 2025
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Ryan K Krueger and Max Ward
Published: 25 April 2025
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Wei Zhang and others
Published: 24 April 2025
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Boyu Lyu and others
Published: 24 April 2025
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Quentin Rouger and others
Bioinformatics Advances, vbaf090, https://doi.org/10.1093/bioadv/vbaf090
Published: 24 April 2025
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ACCEPTED MANUSCRIPT
Tram N Nguyen and others
Bioinformatics Advances, vbaf093, https://doi.org/10.1093/bioadv/vbaf093
Published: 23 April 2025
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Alexander J Petri and Kristoffer Sahlin
Published: 23 April 2025
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Nikolaos Nakis and others
Published: 23 April 2025
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Kaiyuan Yang and others
Published: 23 April 2025
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ACCEPTED MANUSCRIPT
Misung Yi and others
Published: 21 April 2025
Image
Published: 18 April 2025
Figure 1. Flowchart illustrating genome-wide causal gene searches using HORNET. Example options given to flags that the command line version of HORNET uses are at the bottom of each panel. In the “Input data” section, ±1 Mb is used because it is standard in many publicly available data such as GTEx (2015) and
Image
Published: 18 April 2025
Figure 3. This figure illustrates the adjustments for CHP and inflation that are introduced when the eQTLs used in MR are in LD and researchers only have access to relatively small reference panels. (A) The goal of eQTL-MVMR is to estimate θ , which may be subject to bias when Λ and η are eac