📄

Paper

SAAFEC-SEQ: A Sequence-Based Method for Predicting the Effect of Single Point Mutations on Protein Thermodynamic Stability

by Independent / Community 0038b4f00ee1d90b00b7aa05bbe32e77d7c14a2a

Free2AITools Nexus Index

70.1

S: Semantic 50

Query-time baseline · scored live at search

A: Authority 87

P: Popularity 63

R: Recency 100

Q: Quality 65

Tech Context

Vital Performance —

Modeling the effect of mutations on protein thermodynamics stability is useful for protein engineering and understanding molecular mechanisms of disease-causing variants. Here, we report a new development of the SAAFEC method, the SAAFEC-SEQ, which is a gradient boosting decision tree machine learning method to predict the change of the folding free energy caused by amino acid substitutions. The method does not require the 3D structure of the corresponding protein, but only its sequence and, ...

Source →

Semantic Scholar 104 Citations

Paper Information Summary
Entity Passport
Registry ID	0038b4f00ee1d90b00b7aa05bbe32e77d7c14a2a
License	ArXiv
Provider	semantic_scholar

📜

Cite this paper

Academic & Research Attribution

BibTeX

@misc{0038b4f00ee1d90b00b7aa05bbe32e77d7c14a2a,
  author = {Unknown},
  title = {SAAFEC-SEQ: A Sequence-Based Method for Predicting the Effect of Single Point Mutations on Protein Thermodynamic Stability Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/0038b4f00ee1d90b00b7aa05bbe32e77d7c14a2a}},
  note = {Accessed via Free2AITools.}
}

APA Style

Unknown. (2026). SAAFEC-SEQ: A Sequence-Based Method for Predicting the Effect of Single Point Mutations on Protein Thermodynamic Stability [Paper]. Free2AITools. https://api.semanticscholar.org/0038b4f00ee1d90b00b7aa05bbe32e77d7c14a2a

🔬Technical Deep Dive

Full Specifications [+]

⚖️ Free2AITools Nexus Index V2.0

Methodology How FNI works

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 87

Popularity (P) 63

Recency (R) 100

Quality (Q) 65

💬 Index Insight

FNI V2.0 for SAAFEC-SEQ: A Sequence-Based Method for Predicting the Effect of Single Point Mutations on Protein Thermodynamic Stability: Authority (A:87), Popularity (P:63), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology

Open data Updated: Live data

📝 Executive Summary

"Modeling the effect of mutations on protein thermodynamics stability is useful for protein engineering and understanding molecular mechanisms of disease-causing variants. Here, we report a new development of the SAAFEC method, the SAAFEC-SEQ, which is a gradient boosting decision tree machine learning method to predict the change of the folding free energy caused by amino acid substitutions. The method does not require the 3D structure of the corresponding protein, but only its sequence and, ..."

❝ Cite Node

@article{Unknown2026SAAFEC-SEQ:,
  title={SAAFEC-SEQ: A Sequence-Based Method for Predicting the Effect of Single Point Mutations on Protein Thermodynamic Stability},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

🔗 Full Paper

Free2AITools indexes the abstract and factual metadata for this paper. Read the complete, authoritative paper on the official source.

Read the full paper on arXiv

📊 Research Signals

📈104CitationsSemantic Scholar

🏛️87AuthorityFNI pillar

⏱️100RecencyFNI pillar

✅65QualityFNI pillar

🗂️text generationField

📦Data Source: semantic_scholar

🔄 Updated daily

Source summary: Based on semantic_scholar metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Paper Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

source: semantic_scholar
author: Unknown
license: ArXiv
tags: paper, research, academic

⚙️ Technical Specs

architecture: null
params billions: null
context length: null
pipeline tag

📊 Engagement & Metrics

downloads: 0
stars: null
forks: null
citations: 104

Data indexed from public sources. Updated daily.