Explanation

bs-score Score

This section explains how does pdb-profiling define a weighted score that measure the correspondence between the UniProt Isoform and the PDB chain instance (apo-state) in the sequence-level.

UniProt Isoform

This section explains why does pdb-profiling implement SIFTS’s api/mappings/all_isoforms/ API that mapped with all the available alternative products of a UniProt Entry in the Selection pipeline.

• From the point of transcript mapping
• From the point of the best-mapped isoform of a PDB Entity

UniProt Isoform Interaction

This section explains why does pdb-profiling includes isoform-level interaction instead of just focuses on canonical interaction.

Asymmetric Unit & Biological Unit

This section explains why does pdb-profiling not only includes interaction data from asymmetric unit but also from those author/software defined biological assembly. Besides, this section also shows the barriers that pdb-profiling overcame in the process of integrating biological assembly information.

Metrics that measure the similarity/distance between two ranges

This section explains:

1. the ranges/intervals-format that pdb-profiling implements for the representation of sequence coverage range on a reference sequence
2. which metric pdb-profiling apply to measure the similarity/distance between two ranges in different situation and why

Selection Algorithm

This section explains the greedy algorithm that pdb-profiling implements to yield a non-redundant set of coverage ranges, which can be used to define the representative set of protein structures in different polymer forms.

Programming Details

This section explains the key points of pdb-profiling's programming design and architecture, including:

1. Implement Coroutine & Asynchronous Programming
2. Take both of the advantages of file system and database system

Comparison

This section compares pdb-profiling with previous similar works and emphasis on how pdb-profiling overcoming their short-comings.