iCyagen: Your Intelligent Research Partner

Gene-editing model design often gets stuck on strategy, key parameters, target selection, and validation. iCyagen AI turns your request into a design-ready question and helps determine whether KO/cKO, point mutation, microRNA knockout, or cell knockout is the right path. With enough information, it provides a strategy outline, rationale, validation suggestions, and risk notes; otherwise, it asks for the missing parameters first. It helps quickly assess feasibility before project planning, quotation, or experiment design.

ASO design often gets stuck on target-region selection, mechanism choice, and candidate prioritization. ASO Designer supports exon skipping, exon inclusion, and mRNA degradation strategies, generating candidate ASO sequences with predicted efficacy scores. It brings together GC content, target-region distribution, and scoring results so low-potential options can be filtered out early. It is useful for narrowing the candidate list before experiments and focusing validation resources on more promising sequences.

Some variants may not directly change the protein sequence, but can disrupt splice sites and cause exon skipping, intron retention, or abnormal transcripts. RNA Splicer predicts whether a variant may alter mRNA splicing based on the gene, transcript, and mutation information. It shows predicted splice-pattern changes, key scores, and visual position context to help decide whether the variant deserves further functional validation. It is useful for variant interpretation, mechanism research, and pre-analysis before reporting.

Genetic variants may alter amino‑acid sequences and disrupt protein conformations, triggering protein dysfunction and disease. Pathogenicity Predictor leverages AI and authoritative multi‑omics databases to compute variant pathogenic probabilities, output five‑tier clinical classifications and gene‑protein visualizations.