Articles

OMeta: an ontology-based, data-driven metadata tracking system

The development of high-throughput sequencing and analysis has accelerated multi-omics studies of thousands of microbial species, metagenomes, and infectious disease pathogens. Omics studies are enabling genot...

Authors: Indresh Singh, Mehmet Kuscuoglu, Derek M. Harkins, Granger Sutton, Derrick E. Fouts and Karen E. Nelson

Predicting peptide presentation by major histocompatibility complex class I: an improved machine learning approach to the immunopeptidome

To further our understanding of immunopeptidomics, improved tools are needed to identify peptides presented by major histocompatibility complex class I (MHC-I). Many existing tools are limited by their relianc...

Authors: Kevin Michael Boehm, Bhavneet Bhinder, Vijay Joseph Raja, Noah Dephoure and Olivier Elemento

SeqClone: sequential Monte Carlo based inference of tumor subclones

Tumor samples are heterogeneous. They consist of varying cell populations or subclones and each subclone is characterized with a distinct single nucleotide variant (SNV) profile. This explains the source of ge...

Authors: Oyetunji E. Ogundijo and Xiaodong Wang

The computational prediction of drug-disease interactions using the dual-network L_2,1-CMF method

Predicting drug-disease interactions (DDIs) is time-consuming and expensive. Improving the accuracy of prediction results is necessary, and it is crucial to develop a novel computing technology to predict new ...

Authors: Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Juan Wang, Junliang Shang and Ling-Yun Dai

Image-based classification of plant genus and family for trained and untrained plant species

Modern plant taxonomy reflects phylogenetic relationships among taxa based on proposed morphological and genetic similarities. However, taxonomical relation is not necessarily reflected by close overall resemb...

Authors: Marco Seeland, Michael Rzanny, David Boho, Jana Wäldchen and Patrick Mäder

NCLcomparator: systematically post-screening non-co-linear transcripts (circular, trans-spliced, or fusion RNAs) identified from various detectors

Non-co-linear (NCL) transcripts consist of exonic sequences that are topologically inconsistent with the reference genome in an intragenic fashion (circular or intragenic trans-spliced RNAs) or in an intergenic f...

Authors: Chia-Ying Chen and Trees-Juen Chuang

LimeSeg: a coarse-grained lipid membrane simulation for 3D image segmentation

3D segmentation is often a prerequisite for 3D object display and quantitative measurements. Yet existing voxel-based methods do not directly give information on the object surface or topology. As for spatiall...

Authors: Sarah Machado, Vincent Mercier and Nicolas Chiaruttini

DBS: a fast and informative segmentation algorithm for DNA copy number analysis

Genome-wide DNA copy number changes are the hallmark events in the initiation and progression of cancers. Quantitative analysis of somatic copy number alterations (CNAs) has broad applications in cancer resear...

Authors: Jun Ruan, Zhen Liu, Ming Sun, Yue Wang, Junqiu Yue and Guoqiang Yu

A benchmark study of sequence alignment methods for protein clustering

Protein sequence alignment analyses have become a crucial step for many bioinformatics studies during the past decades. Multiple sequence alignment (MSA) and pair-wise sequence alignment (PSA) are two major ap...

Authors: Yingying Wang, Hongyan Wu and Yunpeng Cai

Constructing a database for the relations between CNV and human genetic diseases via systematic text mining

The detection and interpretation of CNVs are of clinical importance in genetic testing. Several databases and web services are already being used by clinical geneticists to interpret the medical relevance of i...

Authors: Xi Yang, Zhuo Song, Chengkun Wu, Wei Wang, Gen Li, Wei Zhang, Lingqian Wu and Kai Lu

Computational prediction of plasma protein binding of cyclic peptides from small molecule experimental data using sparse modeling techniques

Cyclic peptide-based drug discovery is attracting increasing interest owing to its potential to avoid target protein depletion. In drug discovery, it is important to maintain the biostability of a drug within ...

Authors: Takashi Tajimi, Naoki Wakui, Keisuke Yanagisawa, Yasushi Yoshikawa, Masahito Ohue and Yutaka Akiyama

Convolutional neural network based on SMILES representation of compounds for detecting chemical motif

Previous studies have suggested deep learning to be a highly effective approach for screening lead compounds for new drugs. Several deep learning models have been developed by addressing the use of various kin...

Authors: Maya Hirohara, Yutaka Saito, Yuki Koda, Kengo Sato and Yasubumi Sakakibara

Predicting protein-protein interactions using high-quality non-interacting pairs

Identifying protein-protein interactions (PPIs) is of paramount importance for understanding cellular processes. Machine learning-based approaches have been developed to predict PPIs, but the effectiveness of ...

Authors: Long Zhang, Guoxian Yu, Maozu Guo and Jun Wang

DeepM6ASeq: prediction and characterization of m6A-containing sequences using deep learning

N6-methyladensine (m6A) is a common and abundant RNA methylation modification found in various species. As a type of post-transcriptional methylation, m6A plays an important role in diverse RNA activities such...

Authors: Yiqian Zhang and Michiaki Hamada

Classifying early and late mild cognitive impairment stages of Alzheimer’s disease by fusing default mode networks extracted with multiple seeds

The default mode network (DMN) in resting state has been increasingly used in disease diagnosis since it was found in 2001. Prior work has mainly focused on extracting a single DMN with various techniques. How...

Authors: Shengbing Pei, Jihong Guan and Shuigeng Zhou

PDRLGB: precise DNA-binding residue prediction using a light gradient boosting machine

Identifying specific residues for protein-DNA interactions are of considerable importance to better recognize the binding mechanism of protein-DNA complexes. Despite the fact that many computational DNA-bindin...

Authors: Lei Deng, Juan Pan, Xiaojie Xu, Wenyi Yang, Chuyao Liu and Hui Liu

Identification of pre-microRNAs by characterizing their sequence order evolution information and secondary structure graphs

Distinction between pre-microRNAs (precursor microRNAs) and length-similar pseudo pre-microRNAs can reveal more about the regulatory mechanism of RNA biological processes. Machine learning techniques have been...

Authors: Yuanlin Ma, Zuguo Yu, Guosheng Han, Jinyan Li and Vo Anh

DWNN-RLS: regularized least squares method for predicting circRNA-disease associations

Many evidences have demonstrated that circRNAs (circular RNA) play important roles in controlling gene expression of human, mouse and nematode. More importantly, circRNAs are also involved in many diseases thr...

Authors: Cheng Yan, Jianxin Wang and Fang-Xiang Wu

A latent allocation model for the analysis of microbial composition and disease

Establishing the relationship between microbiota and specific diseases is important but requires appropriate statistical methodology. A specialized feature of microbiome count data is the presence of a large n...

Authors: Ko Abe, Masaaki Hirayama, Kinji Ohno and Teppei Shimamura

Estimating heterogeneous treatment effect by balancing heterogeneity and fitness

Estimating heterogeneous treatment effect is a fundamental problem in biological and medical applications. Recently, several recursive partitioning methods have been proposed to identify the subgroups that res...

Authors: Weijia Zhang, Thuc Duy Le, Lin Liu and Jiuyong Li

Predicting adverse drug reactions of combined medication from heterogeneous pharmacologic databases

Early and accurate identification of potential adverse drug reactions (ADRs) for combined medication is vital for public health. Existing methods either rely on expensive wet-lab experiments or detecting exist...

Authors: Yi Zheng, Hui Peng, Xiaocai Zhang, Zhixun Zhao, Jie Yin and Jinyan Li

In silico design of MHC class I high binding affinity peptides through motifs activation map

Finding peptides with high binding affinity to Class I major histocompatibility complex (MHC-I) attracts intensive research, and it serves a crucial part of developing a better vaccine for precision medicine. ...

Authors: Zhoujian Xiao, Yuwei Zhang, Runsheng Yu, Yin Chen, Xiaosen Jiang, Ziwei Wang and Shuaicheng Li

Single-cell gene expression analysis reveals β-cell dysfunction and deficit mechanisms in type 2 diabetes

Type 2 diabetes (T2D) is one of the most common chronic diseases. Studies on T2D are mainly built upon bulk-cell data analysis, which measures the average gene expression levels for a population of cells and c...

Authors: Lichun Ma and Jie Zheng

miRBaseConverter: an R/Bioconductor package for converting and retrieving miRNA name, accession, sequence and family information in different versions of miRBase

miRBase is the primary repository for published miRNA sequence and annotation data, and serves as the “go-to” place for miRNA research. However, the definition and annotation of miRNAs have been changed signif...

Authors: Taosheng Xu, Ning Su, Lin Liu, Junpeng Zhang, Hongqiang Wang, Weijia Zhang, Jie Gui, Kui Yu, Jiuyong Li and Thuc Duy Le

hoDCA: higher order direct-coupling analysis

Direct-coupling analysis (DCA) is a method for protein contact prediction from sequence information alone. Its underlying principle is parameter estimation for a Hamiltonian interaction function stemming from ...

Authors: Michael Schmidt and Kay Hamacher

Time-lagged Ordered Lasso for network inference

Accurate gene regulatory networks can be used to explain the emergence of different phenotypes, disease mechanisms, and other biological functions. Many methods have been proposed to infer networks from gene e...

Authors: Phan Nguyen and Rosemary Braun

iMEGES: integrated mental-disorder GEnome score by deep neural network for prioritizing the susceptibility genes for mental disorders in personal genomes

A range of rare and common genetic variants have been discovered to be potentially associated with mental diseases, but many more have not been uncovered. Powerful integrative methods are needed to systematica...

Authors: Atlas Khan, Qian Liu and Kai Wang

Large-scale mining disease comorbidity relationships from post-market drug adverse events surveillance data

Systems approaches in studying disease relationship have wide applications in biomedical discovery, such as disease mechanism understanding and drug discovery. The FDA Adverse Event Reporting System (FAERS) co...

Authors: Chunlei Zheng and Rong Xu

A multitask bi-directional RNN model for named entity recognition on Chinese electronic medical records

Electronic Medical Record (EMR) comprises patients’ medical information gathered by medical stuff for providing better health care. Named Entity Recognition (NER) is a sub-field of information extraction aimed...

Authors: Shanta Chowdhury, Xishuang Dong, Lijun Qian, Xiangfang Li, Yi Guan, Jinfeng Yang and Qiubin Yu

Using natural language processing and machine learning to identify breast cancer local recurrence

Identifying local recurrences in breast cancer from patient data sets is important for clinical research and practice. Developing a model using natural language processing and machine learning to identify loca...

Authors: Zexian Zeng, Sasa Espino, Ankita Roy, Xiaoyu Li, Seema A. Khan, Susan E. Clare, Xia Jiang, Richard Neapolitan and Yuan Luo

Application of transfer learning for cancer drug sensitivity prediction

In precision medicine, scarcity of suitable biological data often hinders the design of an appropriate predictive model. In this regard, large scale pharmacogenomics studies, like CCLE and GDSC hold the promis...

Authors: Saugato Rahman Dhruba, Raziur Rahman, Kevin Matlock, Souparno Ghosh and Ranadip Pal

Reconstructing high-resolution chromosome three-dimensional structures by Hi-C complex networks

Hi-C data have been widely used to reconstruct chromosomal three-dimensional (3D) structures. One of the key limitations of Hi-C is the unclear relationship between spatial distance and the number of Hi-C cont...

Authors: Tong Liu and Zheng Wang

DLAD4U: deriving and prioritizing disease lists from PubMed literature

Due to recent technology advancements, disease related knowledge is growing rapidly. It becomes nontrivial to go through all published literature to identify associations between human diseases and genetic, en...

Authors: Junhui Shen, Suhas Vasaikar and Bing Zhang

Evaluation of top-down mass spectral identification with homologous protein sequences

Top-down mass spectrometry has unique advantages in identifying proteoforms with multiple post-translational modifications and/or unknown alterations. Most software tools in this area search top-down mass spec...

Authors: Ziwei Li, Bo He, Qiang Kou, Zhe Wang, Si Wu, Yunlong Liu, Weixing Feng and Xiaowen Liu

A new insight into underlying disease mechanism through semi-parametric latent differential network model

In genomic studies, to investigate how the structure of a genetic network differs between two experiment conditions is a very interesting but challenging problem, especially in high-dimensional setting. Existi...

Authors: Yong He, Jiadong Ji, Lei Xie, Xinsheng Zhang and Fuzhong Xue

The International Conference on Intelligent Biology and Medicine (ICIBM) 2018: bioinformatics towards translational applications

The 2018 International Conference on Intelligent Biology and Medicine (ICIBM 2018) was held on June 10–12, 2018, in Los Angeles, California, USA. The conference consisted of a total of eleven scientific sessio...

Authors: Xiaoming Liu, Lei Xie, Zhijin Wu, Kai Wang, Zhongming Zhao, Jianhua Ruan and Degui Zhi

Predicting adverse drug reactions through interpretable deep learning framework

Adverse drug reactions (ADRs) are unintended and harmful reactions caused by normal uses of drugs. Predicting and preventing ADRs in the early stage of the drug development pipeline can help to enhance drug sa...

Authors: Sanjoy Dey, Heng Luo, Achille Fokoue, Jianying Hu and Ping Zhang

SMARTcleaner: identify and clean off-target signals in SMART ChIP-seq analysis

Noises and artifacts may arise in several steps of the next-generation sequencing (NGS) process. Recently, an NGS library preparation method called SMART, or Switching Mechanism At the 5′ end of the RNA Transcrip...

Authors: Dejian Zhao and Deyou Zheng

Degeneracy and genetic assimilation in RNA evolution

The neutral theory of Motoo Kimura stipulates that evolution is mostly driven by neutral mutations. However adaptive pressure eventually leads to changes in phenotype that involve non-neutral mutations. The re...

Authors: Reza Rezazadegan and Christian Reidys

Web-based design and analysis tools for CRISPR base editing

As a result of its simplicity and high efficiency, the CRISPR-Cas system has been widely used as a genome editing tool. Recently, CRISPR base editors, which consist of deactivated Cas9 (dCas9) or Cas9 nickase ...

Authors: Gue-Ho Hwang, Jeongbin Park, Kayeong Lim, Sunghyun Kim, Jihyeon Yu, Eunchong Yu, Sang-Tae Kim, Roland Eils, Jin-Soo Kim and Sangsu Bae

Fast and scalable neural embedding models for biomedical sentence classification

Biomedical literature is expanding rapidly, and tools that help locate information of interest are needed. To this end, a multitude of different approaches for classifying sentences in biomedical publications ...

Authors: Asan Agibetov, Kathrin Blagec, Hong Xu and Matthias Samwald

MeDEStrand: an improved method to infer genome-wide absolute methylation levels from DNA enrichment data

DNA methylation of CpG dinucleotides is an essential epigenetic modification that plays a key role in transcription. Widely used DNA enrichment-based methods offer high coverage for measuring methylated CpG di...

Authors: Jingting Xu, Shimeng Liu, Ping Yin, Serdar Bulun and Yang Dai

Capturing context-specific regulation in molecular interaction networks

Molecular profiles change in response to perturbations. These changes are coordinated into functional modules via regulatory interactions. The genes and their products within a functional module are expected to b...

Authors: Stephen T. A. Rush and Dirk Repsilber

FELLA: an R package to enrich metabolomics data

Pathway enrichment techniques are useful for understanding experimental metabolomics data. Their purpose is to give context to the affected metabolites in terms of the prior knowledge contained in metabolic pa...

Authors: Sergio Picart-Armada, Francesc Fernández-Albert, Maria Vinaixa, Oscar Yanes and Alexandre Perera-Lluna

Bidirectional long short-term memory with CRF for detecting biomedical event trigger in FastText semantic space

In biomedical information extraction, event extraction plays a crucial role. Biological events are used to describe the dynamic effects or relationships between biological entities such as proteins and genes. ...

Authors: Yan Wang, Jian Wang, Hongfei Lin, Xiwei Tang, Shaowu Zhang and Lishuang Li

An SVM-based method for assessment of transcription factor-DNA complex models

Atomic details of protein-DNA complexes can provide insightful information for better understanding of the function and binding specificity of DNA binding proteins. In addition to experimental methods for solv...

Authors: Rosario I. Corona, Sanjana Sudarshan, Srinivas Aluru and Jun-tao Guo

MicroRNA dysregulational synergistic network: discovering microRNA dysregulatory modules across subtypes in non-small cell lung cancers

The majority of cancer-related deaths are due to lung cancer, and there is a need for reliable diagnostic biomarkers to predict stages in non-small cell lung cancer cases. Recently, microRNAs were found to hav...

Authors: Nhat Tran, Vinay Abhyankar, KyTai Nguyen, Jon Weidanz and Jean Gao

Sparse coding of pathology slides compared to transfer learning with deep neural networks

Histopathology images of tumor biopsies present unique challenges for applying machine learning to the diagnosis and treatment of cancer. The pathology slides are high resolution, often exceeding 1GB, have non...

Authors: Will Fischer, Sanketh S. Moudgalya, Judith D. Cohn, Nga T. T. Nguyen and Garrett T. Kenyon

Computational approaches for Cancer 2017 workshop overview

Authors: Sunita Chandrasekaran and Eric Stahlberg

CAT: computer aided triage improving upon the Bayes risk through ε-refusal triage rules

Manual extraction of information from electronic pathology (epath) reports to populate the Surveillance, Epidemiology, and End Result (SEER) database is labor intensive. Systematizing the data extraction autom...

Authors: Nicolas Hengartner, Leticia Cuellar, Xiao-Cheng Wu, Georgia Tourassi, John Qiu, Blair Christian and Tanmoy Bhattacharya