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EMSuite Server

The RoadMap that you can access below contains 16 algorithms developed by Kihara Lab for structure modeling, validation and refinement of cryo-EM maps. After viewing the RoadMap you can choose any of the 16 algorithms to submit your job. For best results please view the Tutorial before submitting a job. Additionally, you will receive detailed instructions in the submission page on how to interpret output and prepare inputs.

Recent Updates All Updates →
v10.12.2 June 18th, 2026 Published two preprints on BioRxiv (DMcloud & DAQplugin)
v10.12.1 June 3rd, 2026 Job configuration tab is redesigned. Now users can view their input maps, structures, and sequences.
v10.12.0 May 27th, 2026 Released Emap2lig: a deep-learning-based computational tool designed to automatically predict ligand densities in cryo-EM maps and model small-molecule ligands directly into those predicted densities.
Category Structure Type Resolution Methods
Structure Modeling Protein ~5 Å DeepMainMast

~5 Å

DeepMainMast Image
MainMast (single-chain only)

~5 Å

MainMast Image
~15 Å DiffModeler (template input)

~15 Å

DiffModeler Image
DiffModeler (sequence input)

~15 Å

DiffModeler(seq) Image
3-15 Å DMcloud

3-15 Å

DMcloud Image
DNA/RNA ~5 Å CryoREAD

~5 Å

Protein
DNA/RNA
Protein-DNA/RNA Complex
~10 Å CryoZeta

~10 Å

DMcloudComplex

~10 Å

DMcloudComplex Image
~5 Å ComplexModeler

~5 Å

Ligand ~6 Å Emap2lig

~6 Å

Emap2lig logo
Structure Validation Protein ~5 Å DAQ-Score

~5 Å

Structure Refinement Protein ~5 Å DAQ-Refine

~5 Å

Unknown Protein Finding Protein ~5 Å DAQFinder

~5 Å

Secondary Structure Detection Protein 5-10 Å Emap2sec

5-10 Å

Protein-DNA/RNA Complex 5-10 Å Emap2sec+

5-10 Å

Structure Fitting Map vs. Map ~20 Å VESPER

~20 Å

Structure vs. Map ~20 Å VESPER(S2M)

~20 Å




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