Researchers developed PROVEAN, a new algorithm to predict the functional effects of amino acid substitutions and insertions/deletions (indels) in proteins. The algorithm uses an alignment-based score to measure the change in sequence similarity between a query sequence and a homologous protein sequence before and after an amino acid variation. This score helps distinguish between disease-associated variants and common polymorphisms, as well as between deleterious and neutral variants. PROVEAN was tested on datasets from UniProt and showed high accuracy, with an area under the receiver operating characteristic curve (AUC) of approximately 0.85 for both human and non-human protein variations. The algorithm also correlates with the biological activity level of protein variations and can be used to assess the functional impact of amino acid changes. PROVEAN can handle single amino acid substitutions, in-frame insertions, deletions, and multiple substitutions. It was validated using experimental datasets and showed good performance compared to existing tools like SIFT, PolyPhen-2, and Mutation Assessor. The algorithm's delta alignment score approach considers sequence context and neighborhood regions, allowing it to predict the effects of various types of sequence variations. PROVEAN is available online at http://provean.jcvi.org.Researchers developed PROVEAN, a new algorithm to predict the functional effects of amino acid substitutions and insertions/deletions (indels) in proteins. The algorithm uses an alignment-based score to measure the change in sequence similarity between a query sequence and a homologous protein sequence before and after an amino acid variation. This score helps distinguish between disease-associated variants and common polymorphisms, as well as between deleterious and neutral variants. PROVEAN was tested on datasets from UniProt and showed high accuracy, with an area under the receiver operating characteristic curve (AUC) of approximately 0.85 for both human and non-human protein variations. The algorithm also correlates with the biological activity level of protein variations and can be used to assess the functional impact of amino acid changes. PROVEAN can handle single amino acid substitutions, in-frame insertions, deletions, and multiple substitutions. It was validated using experimental datasets and showed good performance compared to existing tools like SIFT, PolyPhen-2, and Mutation Assessor. The algorithm's delta alignment score approach considers sequence context and neighborhood regions, allowing it to predict the effects of various types of sequence variations. PROVEAN is available online at http://provean.jcvi.org.