Metagenomic and metabolomic analyses reveal distinct stage-specific phenotypes of the gut microbiota in colorectal cancer
By S. Yachida, Sayaka Mizutani, H. Shiroma, Satoshi Shiba, T. Nakajima, T. Sakamoto, Hikaru Watanabe, Keigo Masuda, Y. Nishimoto, Masaru Kubo and 20 more. Nature Medicine, 2019
1,198 citations recorded by the source corpus.
Subfields: Molecular Biology, Oncology
View Paper: https://www.semanticscholar.org/paper/1c6c1c5745d9105341dc214f4c205ed01b611040
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- Curtis Huttenhower
- Nicola Segata
- Eric A. Franzosa
- F. Asnicar
- George Weingart
- F. Beghini
- Moreno Zolfo
- Paolo Manghi
Citations in the corpus
- Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment (2021, methodology): “, 2019), and finally, to support the use of microbial communities to stratify patients by the characterization of state-specific microbial signatures (Koohi-Moghadam et al., 2019; Wirbel et al., 2019; Yachida et al., 2019).”
- Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2020, methodology): “…cohorts for a total of 1,262 samples (600 control and 662 CRC samples) from 9 different datasets spanning 8 different countries (Feng et al., 2015; Gupta et al., 2019; Thomas et al., 2019; Vogtmann et al., 2016; Wirbel et al., 2019; Yachida et al., 2019; Yu et al., 2017; Zeller et al., 2014) .”