Articles

Analysis and prediction of human acetylation using a cascade classifier based on support vector machine

Acetylation on lysine is a widespread post-translational modification which is reversible and plays a crucial role in some biological activities. To better understand the mechanism, it is necessary to identify...

Authors: Qiao Ning, Miao Yu, Jinchao Ji, Zhiqiang Ma and Xiaowei Zhao

FastProNGS: fast preprocessing of next-generation sequencing reads

Next-generation sequencing technology is developing rapidly and the vast amount of data that is generated needs to be preprocessed for downstream analyses. However, until now, software that can efficiently mak...

Authors: Xiaoshuang Liu, Zhenhe Yan, Chao Wu, Yang Yang, Xiaomin Li and Guangxin Zhang

Laboratory information management software for engineered mini-protein therapeutic workflow

Protein based therapeutics are one of the fastest growing classes of novel medical interventions in areas such as cancer, infectious disease, and inflammation. Protein engineering plays an important role in th...

Authors: Mi-Youn Brusniak, Hector Ramos, Bernard Lee and James M. Olson

Performance assessment of variant calling pipelines using human whole exome sequencing and simulated data

Whole exome sequencing (WES) is a cost-effective method that identifies clinical variants but it demands accurate variant caller tools. Currently available tools have variable accuracy in predicting specific c...

Authors: Manojkumar Kumaran, Umadevi Subramanian and Bharanidharan Devarajan

DeepACLSTM: deep asymmetric convolutional long short-term memory neural models for protein secondary structure prediction

Protein secondary structure (PSS) is critical to further predict the tertiary structure, understand protein function and design drugs. However, experimental techniques of PSS are time consuming and expensive, ...

Authors: Yanbu Guo, Weihua Li, Bingyi Wang, Huiqing Liu and Dongming Zhou

Periodicity and dosage optimization of an RNAi model in eukaryotes cells

As a highly efficient and specific gene regulation technology, RNAi has broad application fields and good prospects. The effect of RNAi enhances as the dosage of siRNA increases, while an exorbitant siRNA dosa...

Authors: Tongle Ma, Yongzhen Pei, Changguo Li and Meixia Zhu

Combining learning and constraints for genome-wide protein annotation

The advent of high-throughput experimental techniques paved the way to genome-wide computational analysis and predictive annotation studies. When considering the joint annotation of a large set of related enti...

Authors: Stefano Teso, Luca Masera, Michelangelo Diligenti and Andrea Passerini

Aneuvis: web-based exploration of numerical chromosomal variation in single cells

Numerical chromosomal variation is a hallmark of populations of malignant cells. Identifying the factors that promote numerical chromosomal variation is important for understanding mechanisms of carcinogenesis...

Authors: Daniel G. Piqué, Grasiella A. Andriani, Elaine Maggi, Samuel E. Zimmerman, John M. Greally, Cristina Montagna and Jessica C. Mar

Filtering procedures for untargeted LC-MS metabolomics data

Untargeted metabolomics datasets contain large proportions of uninformative features that can impede subsequent statistical analysis such as biomarker discovery and metabolic pathway analysis. Thus, there is a...

Authors: Courtney Schiffman, Lauren Petrick, Kelsi Perttula, Yukiko Yano, Henrik Carlsson, Todd Whitehead, Catherine Metayer, Josie Hayes, Stephen Rappaport and Sandrine Dudoit

fastJT: An R package for robust and efficient feature selection for machine learning and genome-wide association studies

Parametric feature selection methods for machine learning and association studies based on genetic data are not robust with respect to outliers or influential observations. While rank-based, distribution-free ...

Authors: Jiaxing Lin, Alexander Sibley, Ivo Shterev, Andrew Nixon, Federico Innocenti, Cliburn Chan and Kouros Owzar

Prediction of activity and specificity of CRISPR-Cpf1 using convolutional deep learning neural networks

CRISPR-Cpf1 has recently been reported as another RNA-guided endonuclease of class 2 CRISPR-Cas system, which expands the molecular biology toolkit for genome editing. However, most of the online tools and app...

Authors: Jiesi Luo, Wei Chen, Li Xue and Bin Tang

pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components

Principal component analysis (PCA) is frequently used in genomics applications for quality assessment and exploratory analysis in high-dimensional data, such as RNA sequencing (RNA-seq) gene expression assays....

Authors: Federico Marini and Harald Binder

Enhancing ontology-driven diagnostic reasoning with a symptom-dependency-aware Naïve Bayes classifier

Ontology has attracted substantial attention from both academia and industry. Handling uncertainty reasoning is important in researching ontology. For example, when a patient is suffering from cirrhosis, the a...

Authors: Ying Shen, Yaliang Li, Hai-Tao Zheng, Buzhou Tang and Min Yang

Difficulty in inferring microbial community structure based on co-occurrence network approaches

Co-occurrence networks—ecological associations between sampled populations of microbial communities inferred from taxonomic composition data obtained from high-throughput sequencing techniques—are widely used ...

Authors: Hokuto Hirano and Kazuhiro Takemoto

Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks

Detection of central nodes in asymmetrically directed biological networks depends on centrality metrics quantifying individual nodes’ importance in a network. In topological analyses on metabolic networks, var...

Authors: Eun-Youn Kim, Daniel Ashlock and Sung Ho Yoon

Bayesian model selection for the Drosophila gap gene network

The gap gene system controls the early cascade of the segmentation pathway in Drosophila melanogaster as well as other insects. Owing to its tractability and key role in embryo patterning, this system has been th...

Authors: Asif Zubair, I. Gary Rosen, Sergey V. Nuzhdin and Paul Marjoram

AutoCryoPicker: an unsupervised learning approach for fully automated single particle picking in Cryo-EM images

An important task of macromolecular structure determination by cryo-electron microscopy (cryo-EM) is the identification of single particles in micrographs (particle picking). Due to the necessity of human invo...

Authors: Adil Al-Azzawi, Anes Ouadou, John J. Tanner and Jianlin Cheng

A dropout-regularized classifier development approach optimized for precision medicine test discovery from omics data

Modern genomic and proteomic profiling methods produce large amounts of data from tissue and blood-based samples that are of potential utility for improving patient care. However, the design of precision medic...

Authors: Joanna Roder, Carlos Oliveira, Lelia Net, Maxim Tsypin, Benjamin Linstid and Heinrich Roder

Statistical representation models for mutation information within genomic data

As DNA sequencing technologies are improving and getting cheaper, genomic data can be utilized for diagnosis of many diseases such as cancer. Human raw genome data is huge in size for computational systems. Th...

Authors: N. Özlem ÖZCAN ŞİMŞEK, Arzucan ÖZGÜR and Fikret GÜRGEN

CLoDSA: a tool for augmentation in classification, localization, detection, semantic segmentation and instance segmentation tasks

Deep learning techniques have been successfully applied to bioimaging problems; however, these methods are highly data demanding. An approach to deal with the lack of data and avoid overfitting is the applicat...

Authors: Ángela Casado-García, César Domínguez, Manuel García-Domínguez, Jónathan Heras, Adrián Inés, Eloy Mata and Vico Pascual

The Kendrick modelling platform: language abstractions and tools for epidemiology

Mathematical and computational models are widely used to study the transmission, pathogenicity, and propagation of infectious diseases. Unfortunately, complex mathematical models are difficult to define, reuse...

Authors: Mai Anh BUI T., Nick Papoulias, Serge Stinckwich, Mikal Ziane and Benjamin Roche

ProteinNet: a standardized data set for machine learning of protein structure

Rapid progress in deep learning has spurred its application to bioinformatics problems including protein structure prediction and design. In classic machine learning problems like computer vision, progress has...

Authors: Mohammed AlQuraishi

Taxonomy based performance metrics for evaluating taxonomic assignment methods

Metagenomics experiments often make inferences about microbial communities by sequencing 16S and 18S rRNA, and taxonomic assignment is a fundamental step in such studies. This paper addresses the weaknesses in...

Authors: Chung-Yen Chen, Sen-Lin Tang and Seng-Cho T. Chou

WellInverter: a web application for the analysis of fluorescent reporter gene data

Fluorescent reporter genes have become widely used for monitoring gene expression in living cells. When a microbial strain carrying a reporter gene is grown in a microplate reader, the fluorescence and the abs...

Authors: Yannick Martin, Michel Page, Christophe Blanchet and Hidde de Jong

Protein-protein interaction prediction using a hybrid feature representation and a stacked generalization scheme

Although various machine learning-based predictors have been developed for estimating protein–protein interactions, their performances vary with dataset and species, and are affected by two primary aspects: ch...

Authors: Kuan-Hsi Chen, Tsai-Feng Wang and Yuh-Jyh Hu

Dynamic genome-scale cell-specific metabolic models reveal novel inter-cellular and intra-cellular metabolic communications during ovarian follicle development

The maturation of the female germ cell, the oocyte, requires the synthesis and storing of all the necessary metabolites to support multiple divisions after fertilization. Oocyte maturation is only possible in ...

Authors: Beatriz Peñalver Bernabé, Ines Thiele, Eugene Galdones, Anaar Siletz, Sriram Chandrasekaran, Teresa K. Woodruff, Linda J. Broadbelt and Lonnie D. Shea

edge2vec: Representation learning using edge semantics for biomedical knowledge discovery

Representation learning provides new and powerful graph analytical approaches and tools for the highly valued data science challenge of mining knowledge graphs. Since previous graph analytical methods have mos...

Authors: Zheng Gao, Gang Fu, Chunping Ouyang, Satoshi Tsutsui, Xiaozhong Liu, Jeremy Yang, Christopher Gessner, Brian Foote, David Wild, Ying Ding and Qi Yu

An advanced approach to identify antimicrobial peptides and their function types for penaeus through machine learning strategies

Antimicrobial peptides (AMPs) are essential components of the innate immune system and can protect the host from various pathogenic bacteria. The marine environment is known to be one of the richest sources fo...

Authors: Yuan Lin, Yinyin Cai, Juan Liu, Chen Lin and Xiangrong Liu

A new fruit fly optimization algorithm enhanced support vector machine for diagnosis of breast cancer based on high-level features

It is of great clinical significance to develop an accurate computer aided system to accurately diagnose the breast cancer. In this study, an enhanced machine learning framework is established to diagnose the ...

Authors: Hui Huang, Xi’an Feng, Suying Zhou, Jionghui Jiang, Huiling Chen, Yuping Li and Chengye Li

A hybrid gene selection method based on gene scoring strategy and improved particle swarm optimization

Gene selection is one of the critical steps in the course of the classification of microarray data. Since particle swarm optimization has no complicated evolutionary operators and fewer parameters need to be a...

Authors: Fei Han, Di Tang, Yu-Wen-Tian Sun, Zhun Cheng, Jing Jiang and Qiu-Wei Li

Scoring amino acid mutation to predict pandemic risk of avian influenza virus

Avian influenza virus can directly cross species barriers and infect humans with high fatality. As antigen novelty for human host, the public health is being challenged seriously. The pandemic risk of avian in...

Authors: Xiaoli Qiang and Zheng Kou

L_2,1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions

Predicting drug-target interactions is time-consuming and expensive. It is important to present the accuracy of the calculation method. There are many algorithms to predict global interactions, some of which u...

Authors: Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai and Sha-Sha Yuan

Preface

Authors: Henry Han and Wenbin Liu

Probe computing model based on small molecular switch

DNA is a promising candidate for the construction of biological devices due to its unique properties, including structural simplicity, convenient synthesis, high flexibility, and predictable behavior. And DNA ...

Authors: Yanan Wang, Qi Lv, Yingying Zhang, Luhui Wang and Yafei Dong

Combining gene ontology with deep neural networks to enhance the clustering of single cell RNA-Seq data

Single cell RNA sequencing (scRNA-seq) is applied to assay the individual transcriptomes of large numbers of cells. The gene expression at single-cell level provides an opportunity for better understanding of ...

Authors: Jiajie Peng, Xiaoyu Wang and Xuequn Shang

Integrated entropy-based approach for analyzing exons and introns in DNA sequences

Numerous essential algorithms and methods, including entropy-based quantitative methods, have been developed to analyze complex DNA sequences since the last decade. Exons and introns are the most notable compo...

Authors: Junyi Li, Li Zhang, Huinian Li, Yuan Ping, Qingzhe Xu, Rongjie Wang, Renjie Tan, Zhen Wang, Bo Liu and Yadong Wang

BAMSE: Bayesian model selection for tumor phylogeny inference among multiple samples

Intra-tumor heterogeneity is known to contribute to cancer complexity and drug resistance. Understanding the number of distinct subclones and the evolutionary relationships between them is scientifically and c...

Authors: Hosein Toosi, Ali Moeini and Iman Hajirasouliha

Deep convolutional neural networks for mammography: advances, challenges and applications

The limitations of traditional computer-aided detection (CAD) systems for mammography, the extreme importance of early detection of breast cancer and the high impact of the false diagnosis of patients drive re...

Authors: Dina Abdelhafiz, Clifford Yang, Reda Ammar and Sheida Nabavi

Attenuating dependence on structural data in computing protein energy landscapes

Nearly all cellular processes involve proteins structurally rearranging to accommodate molecular partners. The energy landscape underscores the inherent nature of proteins as dynamic molecules interconverting ...

Authors: David Morris, Tatiana Maximova, Erion Plaku and Amarda Shehu

Multi-allelic positional Burrows-Wheeler transform

Recent advances in whole-genome sequencing and SNP array technology have led to the generation of a large amount of genotype data. Large volumes of genotype data will require faster and more efficient methods ...

Authors: Ardalan Naseri, Degui Zhi and Shaojie Zhang

MATria: a unified centrality algorithm

Computing centrality is a foundational concept in social networking that involves finding the most “central” or important nodes. In some biological networks defining importance is difficult, which then creates ch...

Authors: Trevor Cickovski, Vanessa Aguiar-Pulido and Giri Narasimhan

String correction using the Damerau-Levenshtein distance

In the string correction problem, we are to transform one string into another using a set of prescribed edit operations. In string correction using the Damerau-Levenshtein (DL) distance, the permissible edit o...

Authors: Chunchun Zhao and Sartaj Sahni

GRASP2: fast and memory-efficient gene-centric assembly and homolog search for metagenomic sequencing data

A crucial task in metagenomic analysis is to annotate the function and taxonomy of the sequencing reads generated from a microbiome sample. In general, the reads can either be assembled into contigs and search...

Authors: Cuncong Zhong, Youngik Yang and Shibu Yooseph

A computational method to aid the design and analysis of single cell RNA-seq experiments for cell type identification

The advent of single cell RNA sequencing (scRNA-seq) enabled researchers to study transcriptomic activity within individual cells and identify inherent cell types in the sample. Although numerous computational...

Authors: Douglas Abrams, Parveen Kumar, R. Krishna Murthy Karuturi and Joshy George

TAR-VIR: a pipeline for TARgeted VIRal strain reconstruction from metagenomic data

Strain-level RNA virus characterization is essential for developing prevention and treatment strategies. Viral metagenomic data, which can contain sequences of both known and novel viruses, provide new opportu...

Authors: Jiao Chen, Jiating Huang and Yanni Sun

COMBImage2: a parallel computational framework for higher-order drug combination analysis that includes automated plate design, matched filter based object counting and temporal data mining

Pharmacological treatment of complex diseases using more than two drugs is commonplace in the clinic due to better efficacy, decreased toxicity and reduced risk for developing resistance. However, many of thes...

Authors: Efthymia Chantzi, Malin Jarvius, Mia Niklasson, Anna Segerman and Mats G. Gustafsson

Detection and visualization of communities in mass spectrometry imaging data

The spatial distribution and colocalization of functionally related metabolites is analysed in order to investigate the spatial (and functional) aspects of molecular networks. We propose to consider community ...

Authors: Karsten Wüllems, Jan Kölling, Hanna Bednarz, Karsten Niehaus, Volkmar H. Hans and Tim W. Nattkemper

A comparison of three programming languages for a full-fledged next-generation sequencing tool

elPrep is an established multi-threaded framework for preparing SAM and BAM files in sequencing pipelines. To achieve good performance, its software architecture makes only a single pass through a SAM/BAM file...

Authors: Pascal Costanza, Charlotte Herzeel and Wilfried Verachtert

Illumina error correction near highly repetitive DNA regions improves de novo genome assembly

Several standalone error correction tools have been proposed to correct sequencing errors in Illumina data in order to facilitate de novo genome assembly. However, in a recent survey, we showed that state-of-t...

Authors: Mahdi Heydari, Giles Miclotte, Yves Van de Peer and Jan Fostier

A dual controllability analysis of influenza virus-host protein-protein interaction networks for antiviral drug target discovery

Host factors of influenza virus replication are often found in key topological positions within protein-protein interaction networks. This work explores how protein states can be manipulated through controllab...

Authors: Emily E. Ackerman, John F. Alcorn, Takeshi Hase and Jason E. Shoemaker