LncInfo

LncInfo predicts and annotates subcellular localization of long non-coding RNAs (lncRNAs) to support functional inference from sequence, structural, experimental, and database evidence.

Key Features:

• Comprehensive lncRNA repository: Aggregates annotations for long non-coding RNAs, including over 20,000 human lncRNA transcripts identified by high-throughput sequencing technologies.
• Subcellular localization prediction and annotation: Predicts and annotates lncRNA subcellular localization based on sequence and structural features.
• Integration of experimental and computational evidence: Consolidates experimental spatial-distribution data with in silico predictions.
• Algorithms and machine learning: Employs algorithms and machine learning models to infer subcellular locations from sequence and structural inputs.
• Database consolidation: Integrates various databases and computational resources relevant to lncRNA annotation and localization.
• Advanced prediction methodologies: Utilizes advanced prediction methodologies to enhance localization inference.
• Validation gap identification: Highlights accuracy and reliability challenges in localization prediction and the need for experimental validation.

Scientific Applications:

• Functional inference: Use localization annotations to infer potential lncRNA roles and interactions within specific cellular compartments.
• Transcriptome-scale analysis: Contextualize over 20,000 human lncRNA transcripts relative to coding transcripts for comparative studies.
• Disease and pathology studies: Support investigations of lncRNA implications in health and disease by linking localization with function.
• Prioritization for validation: Guide selection of candidate lncRNAs for experimental validation of subcellular localization.

Methodology:

In silico algorithms and machine learning models predict subcellular localization from sequence and structural features, and annotations are consolidated with data from external databases and experimental spatial-distribution datasets.