# IEEE/ACM Transactions on Computational Biology and Bioinformatics

### Early Access Articles

Early Access articles are made available in advance of the final electronic or print versions. Early Access articles are peer reviewed but may not be fully edited. They are fully citable from the moment they appear in IEEE Xplore.

## Filter Results

Displaying Results 1 - 25 of 314
• ### Gene Expressions, Hippocampal Volume Loss and MMSE Scores in Computation of Progression and Pharmacologic Therapy Effects for Alzheimer's Disease

Publication Year: 2018, Page(s): 1
| | PDF (3438 KB)

We build personalized relevance parameterization method (PReP-AD) based on artificial intelligence (AI) techniques to compute Alzheimer's disease (AD) progression for patients at mild cognitive impairment (MCI) stage. Expressions of AD related genes, mini mental state examination (MMSE) scores and hippocampal volume measurements of MCI patients are obtained from Alzheimer's Disease Neuroimaging In... View full abstract»

• ### Detection of Colorectal Carcinoma Based on Microbiota Analysis using Generalized Regression Neural Networks and Nonlinear Feature Selection

Publication Year: 2018, Page(s): 1
| | PDF (3000 KB)

To obtain a screening tool for colorectal cancer (CRC) based on gut microbiota, we seek here to identify an optimal classifier for CRC detection as well as a novel nonlinear feature selection method for determining the most discriminative microbial species. In this study, the intestinal microflora in feces of 141 patients were modeled using general regression neural networks (GRNNs) combined with ... View full abstract»

• ### Cophenetic Median Trees

Publication Year: 2018, Page(s): 1
| | PDF (542 KB)

Median tree inference under path-difference metrics has shown great promise for large-scale phylogeny estimation. Similar to these metrics is the family of cophenetic metrics that originates from a classic dendrogram comparison method introduced more than 50 years ago. Despite the appeal of this family of metrics, the problem of computing median trees under cophenetic metrics has not been analyzed... View full abstract»

• ### Bounded Fuzzy Possibilistic Method reveals information about lung cancer through analysis of metabolomics

Publication Year: 2018, Page(s): 1
| | PDF (792 KB)

Learning methods, such as conventional clustering and classification, have been applied in diagnosing diseases to categorize samples based on their features. Going beyond clustering samples, membership degrees represent to what degree each sample belongs to a cluster. Variation of membership degrees in each cluster provides information about the cluster as a whole and each sample individually whic... View full abstract»

• ### A Gaussian Mixture-Model Exploiting Pathway Knowledge for Dissecting Cancer Heterogeneity

Publication Year: 2018, Page(s): 1
| | PDF (1048 KB)

In this work, we develop a systematic approach for applying pathway knowledge to a multivariate Gaussian mixture model for dissecting a heterogeneous cancer tissue. The downstream transcription factors are selected as observables from available partial pathway knowledge in such a way that the subpopulations produce some differential behavior in response to the drugs selected in the upstream. For e... View full abstract»

• ### Preprocessing Sequence Coverage Data for Precise Detection of Copy Number Variations

Publication Year: 2018, Page(s): 1
| | PDF (3242 KB)

Copy number variation (CNV) is a type of genomic/genetic variation that plays an important role in phenotypic diversity, evolution, and disease susceptibility. Next generation sequencing (NGS) technologies have created an opportunity for more accurate detection of CNVs with higher resolution. However, efficient and precise detection of CNVs remains challenging due to high levels of noise and biase... View full abstract»

• ### Bayesian Data Fusion of Gene Expression and Histone Modification Profiles for Inference of Gene Regulatory Network

Publication Year: 2018, Page(s): 1
| | PDF (2231 KB)

Accurately reconstructing gene regulatory networks (GRNs) from high-throughput gene expression data has been a major challenge in systems biology for decades. Many approaches have been proposed to solve this problem. However, there is still much room for the improvement of GRN inference. Integrating data from different sources is a promising strategy. Epigenetic modifications have a close relation... View full abstract»

• ### Integrating Language Model and Reading Control Gate in BLSTM-CRF for Biomedical Named Entity Recognition

Publication Year: 2018, Page(s): 1
| | PDF (895 KB)

Biomedical named entity recognition (Bio-NER) is an important preliminary step for many biomedical text mining tasks. The current mainstream methods for NER are based on the neural networks to avoid the complex hand-designed features derived from various linguistic analyses. However, these methods ignore some potential sentence-level semantic information and general features of semantic and syntac... View full abstract»

• ### Classification of a DNA Microarray for Diagnosing Cancer Using a Complex Network Based Method

Publication Year: 2018, Page(s): 1
| | PDF (732 KB)

Applications that classify DNA microarray expression data are helpful for diagnosing cancer. Many attempts have been made to analyze these data; however, new methods are needed to obtain better results. In this study, a Complex Network (CN) classifier was exploited to implement the classification task. An algorithm was used to initialize the structure, which allowed input variables to be selected ... View full abstract»

• ### WeCoMXP: Weighted Connectivity Measure Integrating Co-Methylation, Co-Expression and Protein-Protein Interactions for Gene-Module Detection

Publication Year: 2018, Page(s): 1
| | PDF (1761 KB)

The identification of modules (groups of several tightly interconnected genes) in gene interaction network is an essential task for better understanding of the architecture of the whole network. In this article, we develop a novel weighted connectivity measure integrating co-methylation, co-expression and protein-protein interactions (called WeCoMXP) to detect gene-modules for multi-omics dataset.... View full abstract»

• ### Utilising Deep Learning and Genome Wide Association Studies for Epistatic-Driven Preterm Birth Classification in African-American Women

Publication Year: 2018, Page(s): 1
| | PDF (933 KB)

Genome-Wide Association Studies (GWAS) are used to identify statistically significant genetic variants in case-control studies. The main objective is to find single nucleotide polymorphisms (SNPs) that influence a particular phenotype. GWAS use a p-value threshold of$5\star 10^{-8}$to identify highly ranked SNPs. While this approach has proven useful for detecting dis... View full abstract»

• ### Parallel Protein Community Detection in Large-scale PPI Networks Based on Multi-source Learning

Publication Year: 2018, Page(s): 1
| | PDF (4128 KB)

Protein interactions constitute the fundamental building block of almost every life activity. Identifying protein communities from Protein-Protein Interaction (PPI) networks is essential to understand the principles of cellular organization and explore the causes of various diseases. It is critical to integrate multiple data resources to identify reliable protein communities that have biological s... View full abstract»

• ### Probe Efficient Feature Representation of Gapped K-mer Frequency Vectors from Sequences using Deep Neural Networks

Publication Year: 2018, Page(s): 1
| | PDF (1762 KB)

Gapped k-mers frequency vectors (gkm-fv) has been presented for extracting sequence features. Coupled with support vector machine (gkm-SVM), gkm-fvs have been used to achieve effective sequence-based predictions. However, the huge computation of a large kernel matrix prevents it from using large amount of data. And it is unclear how to combine gkm-fvs with other data sources in the context of stri... View full abstract»

• ### Extracting Biomedical Events with Parallel Multi-Pooling Convolutional Neural Networks

Publication Year: 2018, Page(s): 1
| | PDF (1414 KB)

Biomedical event extraction is important for medical research and disease prevention, which has attracted much attention in recent years. Traditionally, most of the state-of-the-art systems have been based on shallow machine learning methods, which require many complex, hand-designed features. In addition, the words encoded by one-hot are unable to represent semantic information. Therefore, we uti... View full abstract»

• ### Softepigen: Primers design web-based tool for MS-HRM technique

Publication Year: 2018, Page(s): 1
| | PDF (625 KB)

Polymerase Chain Reaction (PCR) based techniques for DNA methylation techniques includes MS-HRM technique. Methylation Sensitive High-Resolution Melting (MS-HRM) primer-design requires a set of necessary recommendations for such DNA methylation assessment. However, there were not any available software that allows an automatic design of this kind primers. We present Softepigen, the first complete ... View full abstract»

• ### DFseq: Distribution-free method to detect differential gene expression for RNA-sequencing data

Publication Year: 2018, Page(s): 1
| | PDF (1464 KB)

Many current RNA-sequencing data analysis methods compare expressions one gene at a time, taking little consideration of the correlations among genes. In this study, we propose a method to convert such one-dimensional comparison approaches into a two-dimensional evaluation of the ratio of standard deviations of two constructed random variables. This method allows the identification of differential... View full abstract»

• ### Integration of Multi-omics Data for Gene Regulatory Network Inference and Application to Breast Cancer

Publication Year: 2018, Page(s): 1
| | PDF (1690 KB) |  Media

Underlying a cancer phenotype is a specific gene regulatory network that represents the complex regulatory relationships between genes. However, it remains a challenge to find cancer-related gene regulatory network because of insufficient sample sizes and complex regulatory mechanisms in which gene is influenced by not only other genes but also other biological factors. With the development of hig... View full abstract»

• ### Does relaxing the infinite sites assumption give better tumor phylogenies? An ILP-based comparative approach

Publication Year: 2018, Page(s): 1
| | PDF (2631 KB)

Most of the evolutionary history reconstruction approaches are based on the infinite sites assumption, which states that mutations appear once in the evolutionary history. The Perfect Phylogeny model is the result of the infinite sites assumption and has been widely used to infer cancer evolution. Nonetheless, recent results show that recurrent and back mutations are present in the evolutionary hi... View full abstract»

• ### Inferring Spatial Organization of Individual Topologically Associated Domains via Piecewise Helical Model

Publication Year: 2018, Page(s): 1
| | PDF (1491 KB) |  Media

The recently developed Hi-C technology enables a genome-wide view of chromosome spatial organizations, and has shed deep insights into genome structure and genome function. However, multiple sources of uncertainties make downstream data analysis and interpretation challenging. Specifically, statistical models for inferring three-dimensional (3D) chromosomal structure from Hi-C data are far from th... View full abstract»

• ### Artificial Fish Swarm Optimization Based Method to Identify Essential Proteins

Publication Year: 2018, Page(s): 1
| | PDF (1698 KB)

It is well known that essential proteins play an extremely important role in controlling cellular activities in living organisms. Identifying essential proteins from protein protein interaction (PPI) networks is conducive to the understanding of cellular functions and molecular mechanisms. Hitherto, many essential proteins detection methods have been proposed. Nevertheless, those existing identifi... View full abstract»

• ### Incorporating prior knowledge about genetic variants into the analysis of genetic association data: An empirical Bayes approach

Publication Year: 2018, Page(s): 1
| | PDF (893 KB)

In a genome-wide association study (GWAS), the probability that a single nucleotide polymorphism (SNP) is not associated with a disease is its local false discovery rate (LFDR). The LFDR for each SNP is relative to a reference class of SNPs. For example, the LFDR of an exonic SNP can vary widely depending on whether it is considered relative to the separate reference class of other exonic SNPs or ... View full abstract»

• ### Extension of Partial Gene Transcripts by Iterative Mapping of RNA-Seq Raw Reads

Publication Year: 2018, Page(s): 1
| | PDF (1453 KB) |  Media

Many non-model organisms lack reference genomes and the sequencing and de novo assembly of an organism's transcriptome is an affordable means by which to characterize the coding component of its genome. Despite the advances that have made this possible, assembling a transcriptome without a known reference usually results in a collection of full-length and partial gene transcripts. The downstream a... View full abstract»

• ### Dual-layer Strengthened Collaborative Topic Regression Modeling for Predicting Drug Sensitivity

Publication Year: 2018, Page(s): 1
| | PDF (1455 KB) |  Media

An effective way to facilitate the development of modern oncology precision medicine is the systematical analysis of the known drug sensitivities that have emerged in recent years. Meanwhile, the screening of drug response in cancer cell lines provides an estimable genomic and pharmacological data towards high accuracy prediction. Existing works primarily utilize genomic or functional genomic feat... View full abstract»

• ### Adjacent Y-ion Ratio Distributions and Its Application in Peptide Sequencing

Publication Year: 2018, Page(s): 1
| | PDF (1174 KB)

A scoring function plays a critical role in software for peptide identification with mass spectrometry. We present a general scoring feature that can be incorporated in the scoring functions of other peptide identification software. The scoring feature is based on the intensity ratios between two adjacent y-ions in the spectrum. A method is proposed to obtain the probability distributions of such ... View full abstract»

• ### Exploring Frequented Regions in Pan-Genomic Graphs

Publication Year: 2018, Page(s): 1
| | PDF (1950 KB) |  Media

We consider the problem of identifying regions within a pan-genome De Bruijn graph that are traversed by many sequence paths. We define such regions and the subpaths that traverse them as frequented regions (FRs). In this work, we formalize the FR problem and describe an efficient algorithm for finding FRs. Subsequently, we propose some applications of FRs based on machine-learning and pan-genome ... View full abstract»

## Aims & Scope

This bimonthly publishes archival research results related to the algorithmic, mathematical, statistical, and computational methods that are central in bioinformatics and computational biology.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Aidong Zhang, PhD, IEEE Fellow
Dept. of Computer Science and Engineering
State University of New York at Buffalo
Buffalo, New York 14260 USA
azhang@buffalo.edu

Associate Editor-in-Chief
Sun Kim
Seoul National University
sunkim.bioinfo@snu.ac.kr