Functional clustering articles from across Nature Portfolio

Functional clustering is a computational technique that groups samples, for instance proteins, into clusters with similar functions. Clustering is the first step in forming a network of functions, and can help to identify new connections between, for example, different proteins in a cell.

Latest Research and Reviews

Research
11 March 2023 | Open Access

Functional non-parametric mixed effects models for cytotoxicity assessment and clustering
- Tiantian Ma
- , Dan Richard
- & Cristina Anton
Scientific Reports 13, 4075
Research
27 February 2023 | Open Access

Disentangling clustering configuration intricacies for divergently selected chicken breeds
- Anatoly B. Vakhrameev
- , Valeriy G. Narushin
- & Michael N. Romanov
Scientific Reports 13, 3319
Research
17 February 2023 | Open Access

Copy number variation-associated lncRNAs may contribute to the etiologies of congenital heart disease

A transcriptomic analysis of lncRNAs within copy-number variations identifies HSALNG0104472 as a potential lncRNA effector of cardiac defects in non-syndromic congenital heart disease.
- Yibo Lu
- , Qing Fang
- & Bo Wang
Communications Biology 6, 189
Research
04 February 2023 | Open Access

Identification of essential genes and immune cell infiltration in rheumatoid arthritis by bioinformatics analysis
- You Ao
- , Zhongbo Wang
- & Wei Zhang
Scientific Reports 13, 2032
Research
27 January 2023 | Open Access

Resistin-like beta reduction is associated to low survival rate and is downregulated by adjuvant therapy in colorectal cancer patients
- Michelino Di Rosa
- , Antonio Di Cataldo
- & Giovanni Li Volti
Scientific Reports 13, 1490
Research
26 January 2023 | Open Access

Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers

Jäger and colleagues analyze single-base substitution and indel mutational signatures across 27 pediatric cancer types, revealing marked differences in mutational patterns compared with adult cancers and insights into underlying molecular mechanisms.
- Venu Thatikonda
- , S. M. Ashiqul Islam
- & Natalie Jäger
Nature Cancer 4, 276-289

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News and Comment

News & Views | 03 October 2022

BIONIC: discovering new biology through deep learning-based network integration

BIONIC (Biological Network Integration using Convolutions) is a scalable deep learning network integration approach that learns and combines diverse data representations across a range of biological network types to consolidate knowledge of gene function. BIONIC outperforms existing integration approaches by capturing biological information more comprehensively and with greater accuracy than previously possible.

Nature Methods 19, 1185-1186
News & Views | 03 June 2019

Cellular diversity in the colon: another brick in the wall

Single-cell RNA profiling of colonic epithelial crypts from healthy volunteers and patients with ulcerative colitis adds pH-regulating colonocytes and goblet cells expressing a major determinant of barrier maintenance to the current arsenal of uncovered colonic epithelial cell types.
- Isabelle Cleynen
- & Debby Laukens
Nature Reviews Gastroenterology & Hepatology 16, 391-392
Research Highlights | 30 May 2019

Comparing trajectory inference methods
- Nicole Rusk
Nature Methods 16, 459
Editorial | 25 March 2019

Optimizing biological inferences from single-cell data

Two recent articles in Nature Reviews Genetics discuss the exciting opportunities of single-cell omics studies but also highlight the importance of appropriate data analysis strategies.

Nature Reviews Genetics 20, 249
Correspondence | 16 October 2017

MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets
- Martin Steinegger
- & Johannes Söding
Nature Biotechnology 35, 1026-1028
News & Views | 11 September 2017

Interpreting the T-cell receptor repertoire

T cell receptor sequence motifs can predict T cell antigen specificity.
- Robert A Holt
Nature Biotechnology 35, 829-830

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Functional clustering articles from across Nature Portfolio

Latest Research and Reviews

Functional non-parametric mixed effects models for cytotoxicity assessment and clustering

Disentangling clustering configuration intricacies for divergently selected chicken breeds

Copy number variation-associated lncRNAs may contribute to the etiologies of congenital heart disease

Identification of essential genes and immune cell infiltration in rheumatoid arthritis by bioinformatics analysis

Resistin-like beta reduction is associated to low survival rate and is downregulated by adjuvant therapy in colorectal cancer patients

Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers

News and Comment

BIONIC: discovering new biology through deep learning-based network integration

Cellular diversity in the colon: another brick in the wall

Comparing trajectory inference methods

Optimizing biological inferences from single-cell data

MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets

Interpreting the T-cell receptor repertoire

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