BIG: Biological Sequence Analysis Platform

About us

...
Bin Liu's lab at Beijing Institute of Technology (BIT) is focusing on applying the natural language processing techniques to bioinformatics. The research areas of Bin Liu's lab include:

1) Proposing the language models of biological sequences;

2) Studying the natural language processing techniques;

3) Developing the computational tools for biological sequence analysis;

4) Protein remote homology detection and fold recognition;

5) Predicting DNA/RNA binding proteins and their binding residues;

6) Disordered protein/region prediction based on sequence labelling models;

7) Predicting noncoding RNA-disease associations;

8) Identifying protein complexes;

9) DNA/RNA sequence analysis.

Web servers



...
BioSeq-Analysis

A platform for DNA, RNA and protein sequence analysis based on machine learning approaches

...
BioSeq-Analysis2.0

An updated platform for analyzing DNA, RNA and protein sequences at sequence level and residue level based ...

...
Pse-in-One

A web server for generating various modes of pseduo components of DNA, RNA, and protein sequences

...
Pse-Analysis

A Python package for DNA/RNA and protein/peptide sequence analysis based on pseudo components and kernel methods

...
repDNA

A Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined ...

...
repRNA

a web server for generating various feature vectors of RNA sequences

...
HITS-PR-HHblits

Protein Remote Homology Detection by Combining PageRank and Hyperlink-Induced Topic Search

...
ProtDet-CCH

Protein remote homology detection by combining Long Short-Term Memory and ranking methods

...
ProDec-BLSTM

Protein Remote Homology Detection based on Bidirectional Long Short-Term Memory

...
dRHP-PseRA

detecting remote homology proteins using profile-based pseudo protein sequence and rank aggregation

...
ProtDec-LTR

Application of Learning to Rank to protein remote homology detection

...
ProtDec-LTR2.0

An improved method for protein remote homology detection by combining pseudo protein and supervised learning to rank

...
ProtDec-LTR3.0

protein remote homology detection by incorporating profile-based features into Learning to Rank

...
SMI-BLAST

A novel supervised search framework based on PSI-BLAST for protein remote homology detection and its application to ...

...
FoldRec-C2C

protein fold recognition by combining cluster-to-cluster model and protein similarity network

...
ProtFold-DFG

protein fold recognition by combining Directed Fusion Graph and PageRank algorithm

...
IDP-Seq2Seq

Identification of Intrinsically Disordered Proteins and Regions based on Sequence to Sequence Learning

...
RFPR-IDP

Reduce the false positive rates for intrinsically disordered protein and region prediction by incorporating ordered proteins

...
iNCRes-MSLM

identifying nucleic acid binding residues in proteins based on multi-label sequence labeling model

...
iDRBP_MMC

identifying DNA-binding proteins and RNA-binding proteins based on multi-label learning model and motif-based ...

...
DeepDRBP-2L

a new genome annotation predictor for identifying DNA-binding proteins and RNA-binding proteins using Convolutional ...

...
PSFM-DBT

identifying DNA-binding proteins by combing position specific frequency matrix and distance-bigram transformation

...
iPromoter-2L

a two-layer predictor for identifying promoters and their types by multi-window-based PseKNC

...
iPromoter-2L2.0

a predictor for identifying promoters and their types by combining Smoothing Cutting Window algorithm and ...

...
iEnhancer-EL

identifying enhancers and their strength with ensemble learning approach

...
iEnhancer-2L

a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition

...
iDNAPro-PseAAC

DNA binding protein identification by combining pseudo amino acid composition and profile-based protein representation

...
iEsGene-ZCPseKNC

identify eseential genes based on Z curve pseudo k-tuple nucleotide composition

...
iRO-3wPseKNC

identify DNA replication origins by three-window-based PseKNC

...
iRO-PsekGCC

identify DNA replication origins based on Pseudo k-tuple GC Composition

...
iDHS-EL

Identifying DNase I hypersensitive sites by fusing three different modes of pseudo nucleotide composition into an ensemble ...

...
iRSpot-EL

identify recombination spots with an ensemble learning approach

...
iPiDi-PUL

identifying Piwi-interacting RNA-disease associations based on Positive Unlabeled Learning

...
iLncRNAdis-FB

a new predictor for identifying lncRNA-disease associations by fusing biological feature blocks through deep neural network

...
miRNA-deKmer

identification of microRNA precursor with the degenerate K-tuple or Kmer strategy

...
iMiRNA-PseDPC

microRNA precursor identification with a pseudo distance-pair composition approach

...
miRNA-dis

microRNA precursor identification based on distance structure status pairs

...
iMcRNA

identification of the real microRNA precursors with a pseudo structure status composition approach

...
2L-piRNA

a two-layer ensemble classifier identifying piwi-interacting RNAs and their function

...
sgRNA-PSM

predict sgRNAs on-target activity based on Position Specific Mismatch

...
DistanceSVM

Using distances between Top-n-gram and residue pairs for protein remote homology detection

...
PseDNA-Pro

DNA-binding Protein Identification by Combining Chou's PseAAC and Physicochemical Distance Transformation

...
PSSM-DT

Identifying DNA-binding proteins by combining support vector machine and PSSM distance transformation

...
iMiRNA-SSF

Improving the Identification of MicroRNA Precursors by Combining Negative Sets with Different Distributions

...
iDNA-Prot|dis

identifying DNA-binding proteins by incorporating amino acid distance-pairs and reduced alphabet profile into the ...

...
enDNA-Prot

Identification of DNA-binding Proteins by Applying Ensemble Learning

...
remote

Combining evolutionary information extracted from frequency profiles with sequence-based kernels for protein remote ...

Contact

Please constact us by email

Email Us

bliu@bliulab.net