Kuncheng Song

Works (5)

Updated: April 25th, 2025 17:54

2023 journal article

Functional annotation of proteins for signaling network inference in non-model species

Nature Communications, 14(1).

By: L. Van den Broeck n , D. Bhosale n, K. Song n, C. Fonseca de Lima *, M. Ashley  n, T. Zhu *, S. Zhu *, B. Van De Cotte* ...

MeSH headings : Bayes Theorem; Signal Transduction; Transcription Factors / metabolism; Phosphorylation
topics (OpenAlex): Bioinformatics and Genomic Networks; Advanced Proteomics Techniques and Applications; Metabolomics and Mass Spectrometry Studies
TL;DR: A multi-layer neural network that determines protein functionality directly from the protein sequence is developed that shows generalization and scalability and extends to Oryza sativa, Zea mays, Sorghum bicolor, and Triticum aestivum. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries, ORCID, Crossref
Added: September 5, 2023

2023 article

Leveraging Scheme for Cross-Study Microbiome Machine Learning Prediction and Feature Evaluations

Song, K., & Zhou, Y.-H. (2023, February 8). Bioengineering, Vol. 10.

By: K. Song n & Y. Zhou n 

author keywords: feature selection; machine learning; microbiome; random forest; support vector machine; logistic regression
topics (OpenAlex): Gut microbiota and health; Machine Learning in Healthcare; AI in cancer detection
TL;DR: This study developed a method for improving the generalizability and interpretability of machine learning models for predicting three different diseases (colorectal cancer, Crohn’s disease, and immunotherapy response) using nine independent microbiome datasets using random forest as the top model. (via Semantic Scholar)
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Sources: Web Of Science, ORCID, NC State University Libraries
Added: February 10, 2023

2022 article

C3NA: correlation and consensus-based cross-taxonomy network analysis for compositional microbial data

Song, K., & Zhou, Y.-H. (2022, November 8). BMC Bioinformatics, Vol. 11.

By: K. Song n & Y. Zhou n 

author keywords: Co-occurrence network analysis; Microbiome; R package; Consensus clustering; Module preservation analysis
MeSH headings : Phylogeny; Consensus
topics (OpenAlex): Bioinformatics and Genomic Networks; Gut microbiota and health; Metabolomics and Mass Spectrometry Studies
TL;DR: C3NA is presented, a user-friendly R package for investigating compositional microbial sequencing data to identify and compare co-occurrence patterns across different taxonomic levels and discovered clusters of study and disease-dependent taxa that overlap with known functional taxa studied by other discovery studies and differential abundance analyses. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: November 21, 2022

2021 article

The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning

Marvel, S. W., House, J. S., Wheeler, M., Song, K., Zhou, Y.-H., Wright, F. A., … Reif, D. M. (2021, January 1). Environmental Health Perspectives, Vol. 129, pp. 017701–017701-017701–017703.

By: S. Marvel n, J. House* , M. Wheeler *, K. Song n, Y. Zhou n , F. Wright n, W. Chiu *, I. Rusyn *, A. Motsinger-Reif*, D. Reif n 

Contributors: S. Marvel n, J. House* , M. Wheeler *, K. Song n, Y. Zhou n , F. Wright n, W. Chiu *, I. Rusyn *, A. Motsinger-Reif*, D. Reif n 

MeSH headings : COVID-19 / epidemiology; Data Visualization; Health Status Indicators; Humans; Machine Learning; Models, Statistical; Vulnerable Populations
topics (OpenAlex): COVID-19 epidemiological studies; COVID-19 and healthcare impacts; Data-Driven Disease Surveillance
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Sources: Web Of Science, NC State University Libraries, ORCID
Added: March 22, 2021

2020 article

Systematic Comparisons for Composition Profiles, Taxonomic Levels, and Machine Learning Methods for Microbiome-Based Disease Prediction

Song, K., Wright, F. A., & Zhou, Y.-H. (2020, December 16). Frontiers in Molecular Biosciences, Vol. 7.

By: K. Song n, F. Wright n & Y. Zhou n 

author keywords: phenotype prediction; machine learning method; k-mers; operational taxonomic unit (OTU); amplicon sequence variant (ASV); phylogenetic analysis
topics (OpenAlex): Gut microbiota and health; Metabolomics and Mass Spectrometry Studies; Epigenetics and DNA Methylation
TL;DR: The use of short k-mers, which have computational advantages and conceptual simplicity, is shown to be effective as a source for microbiome-based prediction, among machine-learning approaches, and tree-based methods show consistent, though modest, advantages in prediction accuracy. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: January 19, 2021

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