UltraPse

UltraPse generates fixed-length numerical vector representations of biological sequences to enable prediction of biological functions and cellular attributes.


Key Features:

  • Fixed-length conversion: Converts variable-length biological sequences into fixed-length numerical vectors suitable for downstream analysis.
  • Multiple representation modes: Implements multiple existing sequence representation modes for diverse analytical needs.
  • User-defined modes: Allows definition of custom representation modes, physicochemical properties, and sequence types.
  • Extensibility: Provides a modular framework to integrate new representation modes without rewriting existing programs.
  • Support for diverse sequence types: Accommodates various types of biological sequences through customizable representations.
  • Computational efficiency: Optimized for high computational speed in generating sequence representations.

Scientific Applications:

  • Function prediction: Producing input features for predicting biological functions from sequence data.
  • Cellular attribute inference: Enabling prediction of cellular attributes based on sequence-derived vectors.
  • Representation development and evaluation: Facilitating development, customization, and benchmarking of novel sequence representation modes for sequence analysis and downstream predictive tasks.

Methodology:

Generates fixed-length numerical vectors from variable-length sequences by applying multiple sequence representation modes and permitting user-defined representation modes, physicochemical properties, and sequence types.

Topics

Details

License:
GPL-3.0
Tool Type:
command-line tool
Operating Systems:
Linux
Programming Languages:
C++
Added:
7/30/2018
Last Updated:
12/10/2018

Operations

Publications

Du P, Zhao W, Miao Y, Wei L, Wang L. UltraPse: A Universal and Extensible Software Platform for Representing Biological Sequences. International Journal of Molecular Sciences. 2017;18(11):2400. doi:10.3390/ijms18112400. PMID:29135934. PMCID:PMC5713368.

PMID: 29135934
PMCID: PMC5713368
Funding: - National Natural Science Foundation of China: 31401132, 61005041 - Tianjin Natural Science Foundation: 12JCQNJC02300

Documentation