Search our repository of available services.

6 Results

AlphaFold2

Estimated Cost: Around $1.20 for a medium sized protein (~250 AA)

A protein structure prediction model that takes an amino acid sequence, MSA, and a template structure as inputs. Both the MSA and template structure are optional, and inference can be done without them. Additionally, options are available for automating generation of both.


Features

  • Includes 3D interactive visualizations of all your folded protein.
  • Includes interactive visualizations for pLDDT and PAE metrics as well as downloads..
  • Everything from the protein structure, to the MSA used are available for download.
  • Supports monomers and complexes.
  • Supports the faster mmseqs2 MSA algorithm.
  • Supports different MSA databases, single_sequence, and custom MSA.
  • Supports template detection, no templates, as well as custom templates.
  • Supports Amber structure relaxation / refinement.
  • Supports different pairing modes (unpaired+paired, paired, unpaired).
  • Supports different model types (ptm, multimer-v1, multimer-v2).
  • Supports different recycling numbers.

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ProteinMPNN

Estimated Cost: Around $0.10 for 100 samples of a medium sized protein (~250 AA)

ProteinMPNN is a powerful inverse folding model that is capable of not only predicting the amino acids of a protein structure, but also certain chains, and complexes. Additionally, ProteinMPNN can be used as a way to create functional homologs / mutants of existing proteins by inverse folding their structures and sampling the sequence space.


Features

  • Allows you to inverse fold any protein or complex of proteins.
  • Supports homo-oligomers.
  • Includes options to control which chains to design and which to keep fixed.
  • Supports different sampling techniques to better explore the protein landscape.
  • Includes per sequence metrics such as an overall score and sequence recovery.
  • Includes amino acid probabilities by position.
  • Includes sampling temperature adjusted amino acid probabilities by position.

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DiffDock

Estimated Cost: Around $0.15 for 50 predictions

DiffDock is a new state of the art method for molecular docking and drug binding structure prediction. This model takes in a protein structure and ligand as input and returns the ligand docked onto the protein as an output.


Features

  • Predict ligand binding to a protein target of interest.
  • Can be used for drug design as well as domain identification.
  • Includes an interactive 3D protein viewer with the docked ligand.

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ProGen2

Estimated Cost: Around $3.87 for 100 samples of a medium-large sized protein (~512 AA)

ProGen2 is generative protein language model capable of generating de novo proteins and protein variants given an input sequence. Additionally, another version of ProGen2, progen2-oas can be used to generate antibody sequences.


Features

  • Allows you to generate novel proteins or extend existing proteins.
  • Includes options to control the number of output sequences.
  • Supports different sampling techniques to better explore the protein landscape and to diversify prompt outputs.
  • Allows you to specify max length.
  • Includes an output fasta of all the sequences.
  • Includes an output plot of most common residues per residue which can be further interepreted as residue probabilities per position.
  • Includes an output plot likelihoods by sequence.
  • Optimized to execute quickly and efficiently.

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ESM-IF1

Estimated Cost: Around $2.27 for 100 samples of a medium sized protein (~250 AA)

The ESM-IF1 inverse folding model predicts protein sequences from their backbone atom coordinates, trained with 12M protein structures predicted by AlphaFold2.


Features

  • Allows you to inverse fold any protein or complex of proteins.
  • Includes options to control which chains to design and which to keep fixed.
  • Supports different sampling techniques to better explore the protein landscape.
  • Includes per sequence metrics such as an overall score and sequence recovery.
  • Includes amino acid probabilities by position.

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Transcript Assembly

Estimated Cost: Cost varies depending on input size, (usually $20-$30)

Takes in raw transcriptome data from an RNAseq experiment in and automatically assembles and quantifies transcripts. No reference genome required!


Features

  • Automatically assembles raw reads into valid transcripts without requiring a reference genome.
  • Automatically quantifies transcripts.
  • Automatically removes adapters and other unnecessary sequences.
  • Automatically performs quality control on read data.
  • Supports compressed fastq files.

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