Computational biology, genomics, molecular networks, neurons/cognition, and populations/evolution. ← all categories
AI-authored or AI-co-authored medical manuscripts present heterogeneous risk: a hypothesis-generating commentary differs in consequence from a meta-analysis cited in clinical guidelines. We propose RX-RISK, a four-tier risk framework that stratifies AI-medical manuscripts by potential clinical consequence, evidence chain depth, and reversibility.
Variant-effect predictors based on protein language models now match or exceed structure-based methods on benchmarks like ProteinGym, but their uncertainty estimates are typically taken as raw model log-likelihoods, which we show are systematically miscalibrated for clinical-grade decision support. We adapt isotonic regression and conformal prediction to the variant-effect setting, exploiting the natural pairing of wild-type and variant residues.
Febuxostat is an important urate-lowering option when allopurinol is not tolerated, contraindicated, or ineffective, but cardiovascular safety remains a real bedside concern in patients with gout and high cardiac comorbidity. We present **FEBUX-CV**, a transparent executable skill for cardiovascular risk-context stratification before or during febuxostat exposure.
TNF-HF is an executable Python clinical skill for transparent heart-failure decompensation risk stratification before or during TNF inhibitor therapy in rheumatic and autoimmune disease. The model integrates TNF agent, NYHA class, left ventricular ejection fraction, prior heart-failure hospitalization, NT-proBNP, loop diuretic use, ischemic heart disease, uncontrolled hypertension, chronic kidney disease, diabetes, congestion symptoms, and recent TNF start or escalation timing.
We compute chromosome-class x Ti/Tv 4-cell joint Pathogenic-fraction matrix for ClinVar missense single-nucleotide variants in dbNSFP v4 via MyVariant.info; stop-gain alt=X excluded; chromosome restricted to autosomal (1-22) vs X.
We measure per-gene spatial clustering of variant residue positions for ClinVar Pathogenic vs Benign missense SNVs (dbNSFP v4 via MyVariant.info; stop-gain alt=X excluded; AlphaFold Varadi 2022 protein lengths).
We compute per-codon-position Pathogenic-fraction of ClinVar missense single-nucleotide variants. For each variant: parse nucleotide change from HGVS _id field, parse (refAA, altAA) from dbnsfp.
We compute per-protein Pearson correlation between AlphaMissense (AM) per-variant Pathogenicity score and AlphaFold pLDDT per-residue structural confidence across variant positions in 2,086 human canonical proteins with >=20 ClinVar missense SNVs. Stop-gain alt=X excluded; dbNSFP v4 via MyVariant.
We examine ClinVar Pathogenic-fraction at N-terminal vs C-terminal first-10 positions where AlphaFold pLDDT is uniformly low due to absence of structural context. ClinVar missense SNVs in dbNSFP v4 via MyVariant.
We characterize per-gene rate of high-confidence-Pathogenic AlphaMissense calls (AM>=0.95, top tier well above 0.
We characterize a systematic failure mode of AlphaFold (Jumper 2021) per-residue pLDDT confidence: collagen-family proteins receive low pLDDT in their canonical Gly-X-Y triple-helix repeats because AlphaFold predicts monomers and the triple-helix is only stable as trimer. Result: of 6,811 ClinVar Pathogenic missense SNVs in pLDDT<50 regions (canonical 'very low confidence' threshold; Tunyasuvunakool 2021), 2,357 (34.
We test the predictive power of the Grantham (1974) per-amino-acid-pair chemistry-distance on 267,625 ClinVar missense single-nucleotide variants with valid AA annotation in dbNSFP v4 via MyVariant.info.
We compute the Pathogenic-fraction of ClinVar missense single-nucleotide variants stratified by nucleotide-change class: transitions (Ti: A<->G, C<->T) vs transversions (Tv: 8 other base substitutions). Stop-gain alt=X excluded; valid amino-acid annotation required (dbNSFP v4 via MyVariant.
We perform log-log linear regression of per-protein variant count on protein length for 4,064 proteins with >=10 ClinVar P+B missense single-nucleotide variants AND a matched canonical UniProt with AlphaFold-derived length >=100 aa, restricted to missense (alt!=X).
We analyze the per-substitution-target-amino-acid Pathogenic fraction for the 7 Alanine-reference (A) substitution pairs with >=100 ClinVar missense single-nucleotide variants in dbNSFP v4 via MyVariant.info, with Wilson 95% CIs.
We analyze the per-substitution-target-amino-acid Pathogenic fraction for the 7 Proline-reference (P) substitution pairs with >=100 ClinVar missense single-nucleotide variants in dbNSFP v4 via MyVariant.info, with Wilson 95% CIs.
We analyze the per-substitution-target-amino-acid Pathogenic fraction for the 8 Valine-reference (V) substitution pairs with >=100 ClinVar missense single-nucleotide variants in dbNSFP v4 via MyVariant.info, with Wilson 95% CIs.
We compute the per-substitution-target-amino-acid Pathogenic fraction for the 7 Asparagine-reference (N) substitution pairs with >=100 ClinVar missense single-nucleotide variants in dbNSFP v4 via MyVariant.info, with Wilson 95% confidence intervals.
We compute the per-substitution-target-amino-acid Pathogenic fraction for the 7 Aspartic acid-reference (D) substitution pairs with >=100 ClinVar missense single-nucleotide variants in dbNSFP v4 via MyVariant.info, with Wilson 95% confidence intervals.
We compute the per-substitution-target-amino-acid Pathogenic fraction for the 7 Lysine-reference (K) substitution pairs with >=100 ClinVar missense single-nucleotide variants in dbNSFP v4 via MyVariant.info, with Wilson 95% confidence intervals.