BIG: Biological Sequence Analysis Platform

About us

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Bin Liu's lab at Beijing Institute of Technology (BIT) is focusing on developing techniques grounded in the natural language processing (NLP) to uncover the meanings of "book of life". The research areas of Bin Liu's lab include:

1) Developing the Biological language models (BLMs);

2) Studying the natural language processing techniques;

3) Applying BLMs to 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



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BioSeq-Diabolo

biological sequence similarity analysis using Diabolos

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BioSeq-BLM

a platform for analyzing DNA, RNA, and protein sequences based on biological language models

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BioSeq-Analysis2.0

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

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BioSeq-Analysis

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

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Pse-in-One

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

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Pse-Analysis

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

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repDNA

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

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repRNA

a web server for generating various feature vectors of RNA sequences

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HITS-PR-HHblits

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

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ProtDet-CCH

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

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ProDec-BLSTM

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

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dRHP-PseRA

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

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ProtDec-LTR

Application of Learning to Rank to protein remote homology detection

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ProtDec-LTR2.0

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

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ProtDec-LTR3.0

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

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SMI-BLAST

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

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FoldRec-C2C

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

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ProtFold-DFG

protein fold recognition by combining Directed Fusion Graph and PageRank algorithm

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IDP-Seq2Seq

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

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RFPR-IDP

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

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NCBRPred

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

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iDRBP_MMC

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

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DeepDRBP-2L

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

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PSFM-DBT

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

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iPromoter-2L

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

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iPromoter-2L2.0

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

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iEnhancer-EL

identifying enhancers and their strength with ensemble learning approach

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iEnhancer-2L

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

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iDNAPro-PseAAC

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

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iEsGene-ZCPseKNC

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

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iRO-3wPseKNC

identify DNA replication origins by three-window-based PseKNC

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iRO-PsekGCC

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

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iDHS-EL

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

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iRSpot-EL

identify recombination spots with an ensemble learning approach

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iPiDi-PUL

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

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iLncRNAdis-FB

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

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miRNA-deKmer

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

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iMiRNA-PseDPC

microRNA precursor identification with a pseudo distance-pair composition approach

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miRNA-dis

microRNA precursor identification based on distance structure status pairs

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iMcRNA

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

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2L-piRNA

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

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sgRNA-PSM

predict sgRNAs on-target activity based on Position Specific Mismatch

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DistanceSVM

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

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PseDNA-Pro

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

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PSSM-DT

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

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iMiRNA-SSF

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

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iDNA-Prot|dis

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

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enDNA-Prot

Identification of DNA-binding Proteins by Applying Ensemble Learning

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remote

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

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IDRBP-PPCT

Identifying nucleic acid-binding proteins based on PSSM and PSFM Cross Transformation

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iDRBP-EL

identifying DNA-binding proteins and RNA-binding proteins based on hierarchical ensemble learning

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selfAT-fold

protein fold recognition based on residue-based and motif-based self-attention networks

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TransDFL

identification of disordered flexible linker regions in proteins by combining sequence labeling and transfer learning

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PreRBP-TL

prediction of species-specific RNA-binding proteins based on transfer learning

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iCircDA-LTR

identification of circRNA-disease associations based on learning to rank

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ProtRe-CN

Protein remote homology detection by combining classification methods and network methods via Learning to Rank

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DeepIDP-2L

protein intrinsically disordered region prediction by combining convolutional attention network and hierarchical attention network.

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PreTP-EL

prediction of therapeutic peptides based on ensemble learning

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PreTP-Stack

Therapeutic peptides prediction based on auto-weighted multi-view learning

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iSnoDi-LSGT

identifying snoRNA-disease associations based on local similarity constraint and global topological constraint

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iDRNA-ITF

Identifying DNA- and RNA-binding residues in proteins based on induction and transfer framework

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sAMPpred-GAT

Prediction of Antimicrobial Peptides based on Graph Attention Network

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iDRBP-ECHF

Identifying DNA- and RNA- binding proteins based on extensible cubic hybrid framework

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PreHom-PCLM

Protein Remote Homology Detection by Combing Motifs and Protein Cubic Language Model

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iLncDA-LTR

Identification of lncRNA-disease associations by learning to rank

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DMFpred

Predicting protein disorder molecular functions based on protein cubic language model

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GraLTR-LDA

lncRNA-disease association prediction based on graph auto-encoder and Learning to Rank

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iPiDA-LTR

Identifying piwi-interacting RNA-disease associations based on learning to rank

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iPiDA-GCN

Identification of piRNA-disease associations based on Graph Convolutional Network

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iSnoDi-MDRF

Identifying snoRNA-disease associations based on multiple biological data by ranking framework

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idenMD-NRF

A novel ranking framework for improving the identification of miRNA-disease association

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PreTP-2L

Identification of therapeutic peptides and their types using two-layer ensemble learning framework

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ncRNALocate-EL

A novel multi-label Subcellular Locality prediction model of ncRNA based on ensemble learning

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ProFun-SOM

Protein Function Prediction for Specific Ontology based on Multiple Sequence Alignment Reconstruction

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iPiDA-SWGCN

Identification of piRNA-disease associations based on Supplementarily Weighted Graph Convolutional Network

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TPpred-LE

Therapeutic peptide functions prediction based on label embedding

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IDP_LM

Prediction of protein intrinsic disorder and disorder functions based on language models

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DAmiRLocGNet

miRNA subcellular localization prediction by combining miRNA-disease associations and graph convolutional networks

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PDB-BRE

A ligand-protein interaction binding residue extractor based on Protein Data Bank

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IDP-Fusion

Protein intrinsically disordered region prediction by combining Neural Architecture Search and Multi-objective genetic algorithm

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MulStack

An ensemble learning prediction model of multilabel mRNA subcellular localization

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DisoFLAG

Accurate prediction of protein intrinsic disorder and its functions using graph-based interaction protein language model

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iLncDA-PT

Navigating the LncRNA-disease Pipeline: from Disease-associated LncRNA Identification to Prognosis and Therapeutic for Diseases

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IIDL-PepPI

Peptide-Protein Interaction Profiling Model Based on Interpretable Progressive Transfer Model

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MMLmiRLocNet

A Multi-view Multi-label Learning Approach for miRNA Subcellular Localization Prediction

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iDRPro-SC

Identifying DNA-Binding Proteins and RNA-Binding Proteins based on Subfunction Classifiers

Contact

Please constact us by email

Email Us

Prof. Dr. Bin Liu, email: bliu@bliulab.net