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MutationAssessor in cBioPortal

Su, Y.; Li, X.; Reva, B.; Antipin, Y.; Schultz, N.; de Bruijn, I.; Sander, C.

2025-08-12 cancer biology
10.1101/2025.08.10.669566 bioRxiv
Show abstract

MutationAssessor (MA) helps researchers evaluate the likely functional impact of somatic and germline mutations in cancer. It provides an evolution-based functional impact score (FIS) to classify mutations based on their likely effect on protein function. FIS scores are based on analysis of patterns of conservation in protein families (conserved residues) and subfamilies (specificity residues). In this new version (r4) we have (1) refined the combinatorial entropy analysis of conservation patterns, (2) recalculated full-length protein multiple sequence alignments covering a larger fraction of human proteins and making use of the explosive growth of protein sequence data, (3) compared predicted functional impact with the pathogenic-benign classification of sequence variants in curated knowledge bases, such as ClinVar, (4) observed the inverse relationship between predicted high functional impact and variant frequency in germline genome sequences and (5) explore the evaluation of switch-of-function mutational effects. Functional impact of [~]4 million somatic amino-acid changing mutations across more than 320K human tumor samples are now available in the widely used cBioPortal for Cancer Genomics.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Bioinformatics
◐ 1204 papers in training set
Top 1%
17.9%
Similar papers in this journal
2
Bioinformatics Advances
◐ 203 papers in training set
Top 0.1%
14.6%
Similar papers in this journal
3
Molecular Systems Biology
○ 162 papers in training set
Top 0.2%
6.5%
Similar papers in this journal
4
PLOS Computational Biology
● 1863 papers in training set
Top 7%
5.3%
Similar papers in this journal
5
PeerJ
◐ 308 papers in training set
Top 1%
4.2%
Similar papers in this journal
6
Scientific Reports
○ 3612 papers in training set
Top 39%
2.6%
50% of probability mass above
7
NAR Genomics and Bioinformatics
◐ 242 papers in training set
Top 2%
2.4%
8
Genome Medicine
○ 183 papers in training set
Top 2%
2.3%
9
GENETICS
◐ 483 papers in training set
Top 2%
2.1%
10
Human Mutation
○ 34 papers in training set
Top 0.3%
2.1%
11
Life Science Alliance
● 285 papers in training set
Top 3%
2.1%
12
Frontiers in Bioinformatics
○ 49 papers in training set
Top 0.4%
1.8%
13
Communications Biology
○ 993 papers in training set
Top 13%
1.8%
14
Genome Research
● 468 papers in training set
Top 4%
1.7%
15
eLife
● 5828 papers in training set
Top 52%
1.7%
16
European Journal of Human Genetics
○ 58 papers in training set
Top 0.7%
1.6%
17
Nature Communications
○ 5641 papers in training set
Top 46%
1.6%
18
Genome Biology
○ 637 papers in training set
Top 6%
1.6%
19
Nucleic Acids Research
◐ 1281 papers in training set
Top 10%
1.5%
20
NAR Cancer
◐ 37 papers in training set
Top 0.4%
1.5%
21
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 4%
1.5%
22
iScience
○ 1154 papers in training set
Top 29%
1.1%
23
Genome Biology and Evolution
◐ 338 papers in training set
Top 3%
1.1%
24
Frontiers in Molecular Biosciences
○ 102 papers in training set
Top 2%
1.1%
25
Disease Models & Mechanisms
139 papers in training set
Top 2%
1.0%
26
PLOS Genetics
● 862 papers in training set
Top 10%
1.0%
27
International Journal of Molecular Sciences
○ 494 papers in training set
Top 13%
1.0%
28
Biology Open
● 156 papers in training set
Top 3%
1.0%
29
Journal of Molecular Biology
○ 232 papers in training set
Top 3%
1.0%
30
The American Journal of Human Genetics
○ 234 papers in training set
Top 3%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.