You can improve your productivity by using Annotator. Its proprietary algorithms finds the V-Region or V-Gene. Non-annotated sequences are presented in a way that simplifies results interpretation. Results can be viewed in a browser or downloaded for later interpretation.
Simply upload your compressed Ab1. Annotator will extract sequences from the ab1 files and annotate them and export FW1 nucleotide sequences with a single mouse click.
Just set the organism to “Homo sapiens” and have a couple of runs with various settings for stringency, and Annotator will mine the complete non-human VH repertoire for human-like Frameworks in minutes.
The Abcluster algorithm will process your dataset through multiple clustering cycles and generates output results help assess the library diversity.
Just upload you’re your NGS library to Abcluster and it will find and sort the highly expressed chains clusters in one go.
Just upload your Abi zip file to Abaligner. V-Regions are extracted automatically and are aligned using the 3D structure-based alignment tool. Select your sequences and exported them as text, html or Excel file.
Once your VH sequences are uploaded to Abaligner, you obtain the full alignment with Kabat numbering in a plain text file with a single mouse click.
Submit your DNA sequences to Germaligner. V-Region or V-Gene protein sequences are extracted from the dataset and processed. Antibodies from the same germline are grouped into clusters and aligned using Abaligner.
Germaligner will generate a 3D structure-based alignment of your antibody sequences with germlines genes in a user-friendly interface to assist you with your decision making during the humanization processes.
Rely on Abquery to mine the repertoire and find sequence variants. The algorithm displays the results as multiple alignments with statistical data in a visually effective way.
Let Abquery find similar VH sequences. Next, Abaligner will align the sequence hits with the query VH as a consensus sequence. Mutations are clearly visualized in the alignment and the Wu-Kabat variability and the amino acid position-frequency data are generated.
Upload your libraries (they may contain millions of sequences) and let the Pan4Seq algorithm compare them. The algorithm will sort the enriched ones according to specific Pan4Seq parameters and generate a user-friendly report. The approach can also be used to compare two patient populations, “control” and “test”, to find a specific immune fingerprint for a certain pathology.
Let MotifFinder screen the 1200 VH sequences for Endosomal Escape Domains (EED) and extract the VH chains with this EED signature. MotifFinder shows in which feature, Framework or CDR the EED are found.
Starting with DNA VH sequences the Hotspot algorithm computes the amino acid and codon Wu-Kabat variability. Variability is reported as charts, and the raw data is exported in Excel format for further processing.
Provide Abcloner with the following input: The Plasmid and 1 or 2 restriction enzymes. Abcloner will annotate the 192 VH sequence, search for restriction enzymes then cut and extract the V-Region fragment, that will be inserted into the plasmid. The new construct is annotated, and the plasmid features are shifted, taking into account the V-Region insert size. Constructs are reported in a downloadable multiple Genbank file.
The Nanobodies DNA or protein sequences are uploaded into Abparam. All the relevant parameters are calculated and Abparam filter extracts Nanobodies with a low pI and reports the results in Excel format. In a couple of minutes the scientists were able to confirm their hypothesis. All the poorly purifiable Nanobodies were exported in the Excel table for further follow-up work.
gExtractor, a ,machine learning algorithm, finished the job in a single run.