BioSeq-BLM: a platform for analyzing DNA, RNA and protein sequences based on biological language models

iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization

(2021) Zhen Chen et al.   NUCLEIC ACIDS RESEARCH

Improved protein structure prediction using potentials from deep learning

(2020) Andrew W. Senior et al.   NATURE

Accurate Prediction of Genome-wide RNA Secondary Structure Profile Based on Extreme Gradient Boosting

(2020) Yaobin Ke et al.   BIOINFORMATICS

Deep learning for genomics using Janggu

(2020) Wolfgang Kopp et al.   Nature Communications

iDRBP_MMC: Identifying DNA-Binding Proteins and RNA-Binding Proteins Based on Multi-Label Learning Model and Motif-Based Convolutional Neural Network

(2020) Jun Zhang et al.   JOURNAL OF MOLECULAR BIOLOGY

‘It will change everything’: DeepMind’s AI makes gigantic leap in solving protein structures

(2020) Ewen Callaway   NATURE

Grammar of protein domain architectures

(2019) Lijia Yu et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

TriPepSVM: de novo prediction of RNA-binding proteins based on short amino acid motifs

(2019) Annkatrin Bressin et al.   NUCLEIC ACIDS RESEARCH

Selene: a PyTorch-based deep learning library for sequence data

(2019) Kathleen M. Chen et al.   NATURE METHODS

The Kipoi repository accelerates community exchange and reuse of predictive models for genomics

(2019) Žiga Avsec et al.   NATURE BIOTECHNOLOGY

BioSeq-Analysis2.0: an updated platform for analyzing DNA, RNA and protein sequences at sequence level and residue level based on machine learning approaches

(2019) Bin Liu et al.   NUCLEIC ACIDS RESEARCH

MotifCNN-fold: protein fold recognition based on fold-specific features extracted by motif-based convolutional neural networks

(2019) Chen-Chen Li et al.   BRIEFINGS IN BIOINFORMATICS

DeepSVM-fold: protein fold recognition by combining support vector machines and pairwise sequence similarity scores generated by deep learning networks

(2019) Bin Liu et al.   BRIEFINGS IN BIOINFORMATICS

An Efficient Approach based on Multi-sources Information to Predict CircRNA-disease Associations Using Deep Convoltional Neural Network

(2019) Lei Wang et al.   BIOINFORMATICS

Using recursive feature elimination in random forest to account for correlated variables in high dimensional data

(2018) Burcu F. Darst et al.   BMC GENETICS

IDP–CRF: Intrinsically Disordered Protein/Region Identification Based on Conditional Random Fields

(2018) Yumeng Liu et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

M6AMRFS: Robust Prediction of N6-Methyladenosine Sites With Sequence-Based Features in Multiple Species

(2018) Xiaoli Qiang et al.   Frontiers in Genetics

Generalising Ward’s Method for Use with Manhattan Distances

(2017) Trudie Strauss et al.   PLoS One

iDHS-EL: identifying DNase I hypersensitive sites by fusing three different modes of pseudo nucleotide composition into an ensemble learning framework

(2016) Bin Liu et al.   BIOINFORMATICS

Accurate Prediction of Transposon-Derived piRNAs by Integrating Various Sequential and Physicochemical Features

(2016) Longqiang Luo et al.   PLoS One

protr/ProtrWeb: R package and web server for generating various numerical representation schemes of protein sequences

(2015) Nan Xiao et al.   BIOINFORMATICS

Pydna: a simulation and documentation tool for DNA assembly strategies using python

(2015) Filipa Pereira et al.   BMC BIOINFORMATICS

The language of the protein universe

(2015) Andrea Scaiewicz et al.   CURRENT OPINION IN GENETICS & DEVELOPMENT

Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

(2015) Babak Alipanahi et al.   NATURE BIOTECHNOLOGY

Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences

(2015) Bin Liu et al.   NUCLEIC ACIDS RESEARCH

Identification of Real MicroRNA Precursors with a Pseudo Structure Status Composition Approach

(2015) Bin Liu et al.   PLoS One

PseKNC: A flexible web server for generating pseudo K-tuple nucleotide composition

(2014) Wei Chen et al.   ANALYTICAL BIOCHEMISTRY

Rcpi: R/Bioconductor package to generate various descriptors of proteins, compounds and their interactions

(2014) D.-S. Cao et al.   BIOINFORMATICS

PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions

(2014) Wei Chen et al.   BIOINFORMATICS

Use B-factor related features for accurate classification between protein binding interfaces and crystal packing contacts

(2014) Qian Liu et al.   BMC BIOINFORMATICS

PseDNA-Pro: DNA-Binding Protein Identification by Combining Chou’s PseAAC and Physicochemical Distance Transformation

(2014) Bin Liu et al.   Molecular Informatics

iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition

(2014) Hao Lin et al.   NUCLEIC ACIDS RESEARCH

A survey on feature selection methods

(2013) Girish Chandrashekar et al.   COMPUTERS & ELECTRICAL ENGINEERING

Fast image reconstruction with L2-regularization

(2013) Berkin Bilgic et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Probabilistic topic models

(2012) David M. Blei   COMMUNICATIONS OF THE ACM

Preprocessing unbalanced data using support vector machine

(2012) M.A.H. Farquad et al.   DECISION SUPPORT SYSTEMS

Using Amino Acid Physicochemical Distance Transformation for Fast Protein Remote Homology Detection

(2012) Bin Liu et al.   PLoS One

LIBSVM

(2012) Chih-Chung Chang et al.   ACM Transactions on Intelligent Systems and Technology

An assessment of substitution scores for protein profile–profile comparison

(2011) Xugang Ye et al.   BIOINFORMATICS

A comparative study of TF*IDF, LSI and multi-words for text classification

(2010) Wen Zhang et al.   EXPERT SYSTEMS WITH APPLICATIONS

SVM based prediction of RNA-binding proteins using binding residues and evolutionary information

(2010) Manish Kumar et al.   JOURNAL OF MOLECULAR RECOGNITION

A new taxonomy-based protein fold recognition approach based on autocross-covariance transformation

(2009) Qiwen Dong et al.   BIOINFORMATICS

A discriminative method for protein remote homology detection and fold recognition combining Top-n-grams and latent semantic analysis

(2008) Bin Liu et al.   BMC BIOINFORMATICS

Using support vector machine combined with auto covariance to predict protein–protein interactions from protein sequences

(2008) Yanzhi Guo et al.   NUCLEIC ACIDS RESEARCH

DiProDB: a database for dinucleotide properties

(2008) Maik Friedel et al.   NUCLEIC ACIDS RESEARCH

Predicting Human Nucleosome Occupancy from Primary Sequence

(2008) Shobhit Gupta et al.   PLoS Computational Biology