# PLoS Computational Biology

**Type:** Journals  
**Canonical URL:** https://scholariq.org/journals/plos-computational-biology/

## Facts

| Field | Value |
| --- | --- |
| Open Access | true |
| ISSN-L | 1553-734X |
| ISSNs | 1553-734X,1553-7358 |
| OpenAlex ID | https://openalex.org/S86033158 |
| Publisher | Public Library of Science |

## Journal papers

Showing 12 of 17.

- [Predicting Network Activity from High Throughput Metabolomics](https://scholariq.org/papers/predicting-network-activity-from-high-throughput-metabolomics/)
- [Structural Properties of the Caenorhabditis elegans Neuronal Network](https://scholariq.org/papers/structural-properties-of-the-caenorhabditis-elegans-neuronal-network/)
- [Mindboggling morphometry of human brains](https://scholariq.org/papers/mindboggling-morphometry-of-human-brains/)
- [deFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data](https://scholariq.org/papers/defuse-an-algorithm-for-gene-fusion-discovery-in-tumor-rna-seq-data/)
- [Differentiating Protein-Coding and Noncoding RNA: Challenges and Ambiguities](https://scholariq.org/papers/differentiating-protein-coding-and-noncoding-rna-challenges-and-ambiguities/)
- [Chaste: An Open Source C++ Library for Computational Physiology and Biology](https://scholariq.org/papers/chaste-an-open-source-c-library-for-computational-physiology-and-biology/)
- [A Proposal for a Coordinated Effort for the Determination of Brainwide Neuroanatomical Connectivity in Model Organisms at a Mesoscopic Scale](https://scholariq.org/papers/a-proposal-for-a-coordinated-effort-for-the-determination-of-brainwide/)
- [Dynamic Analysis of Integrated Signaling, Metabolic, and Regulatory Networks](https://scholariq.org/papers/dynamic-analysis-of-integrated-signaling-metabolic-and-regulatory-networks/)
- [Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes](https://scholariq.org/papers/google-goes-cancer-improving-outcome-prediction-for-cancer-patients-by-network/)
- [Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes](https://scholariq.org/papers/systematically-benchmarking-peptide-mhc-binding-predictors-from-synthetic-to/)
- [Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment](https://scholariq.org/papers/convolutional-neural-networks-improve-species-distribution-modelling-by/)
- [Visual Nonclassical Receptive Field Effects Emerge from Sparse Coding in a Dynamical System](https://scholariq.org/papers/visual-nonclassical-receptive-field-effects-emerge-from-sparse-coding-in-a/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.