TAXyl (Thermal activity prediction for xylanase)

A sequence-based method for predicting the optimum temperature of activity for xylanases from GH10 and GH11 families

Xylanases are a class of enzymes involved in the process of xylan degradation with a variety of industrial applications. The optimum temperature of any enzyme is one of its most important attributes. Time and resource limitations make it practically impossible to measure the optimum temperature of all enzymes experimentally. Thermal activity prediction for Xylanase (TAXyl) is designed to help researchers in computational prediction of the optimum temperature for xylanase enzymes from glycoside hydrolysis families 10 and 11. TAXyl utilizes a random forest-based machine learning method and it achieved the mean accuracy of ~0.79 through multiple iterations of six-fold cross-validations.


This tool gets input(s) in the forms of single amino acid sequence, single protein entry or FASTA file with single or multiple sequences of xylanases from GH families 10 and 11 and then it returns their probable thermal activity status. For single inputs, the predicted result will be shown on the page and for the FASTA inputs, your results will be downloadable in a text format.

In the results:

  • “non-thermoactive” means the enzyme's optimum temperature is below 50°C.
  • “thermoactive” means the enzyme's optimum temperature is between 50°C and 75°C.
  • “hyper-thermoactive” means the enzyme's optimum temperature is above 75°C.

Feature Extraction and Selection

This tool calculates various protein descriptors and selects the most relevant ones with optimum temperature of the enzyme. These features are saved into a .CSV file which is downloadable. Again it accepts inputs in single protein (sequence or entry) or FASTA format. These features can be used by the user for other research purposes.

Feature Extraction and Selection

your sequence

About Us:

The Complex Biological systems and Bioinformatics (CBB) lab, lead by Kaveh Kavousi, is part of the department of bioinformatics of IBB (Institute of Biochemistry and Biophysics), University of Tehran.

An interdisciplinary group of Ph.D. candidates in Bioinformatics, Biotechnology, Biochemistry, Biophysics, biology, medical sciences, and computer science and engineering, along with master and undergraduate students from various disciplines, through a systematic approach, try to better understand the nature of complex biological systems, ranging from interaction between intra-cellular components to inter-cellular relations in different resolutions and from interactions between organisms to interaction networks within organisms. Inferring and analyzing context-specific metabolic networks, co-expression and co-abundance networks, host-microbiome interactions, and heterogeneous networks are some examples.

Contact Us

The Complex systems and Bioinformatics (CBB) lab is currently located at the Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.




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