Low-mass-ion discriminant equation (LOME) for ovarian cancer screening
A low-mass-ion discriminant equation (LOME) was constructed to investigate whether systematic low-mass-ion (LMI) profiling could be applied to ovarian cancer (OVC) screening. (Source: BioData Mining)
Source: BioData Mining - October 12, 2016 Category: Bioinformatics Authors: Jun Hwa Lee, Byong Chul Yoo, Yun Hwan Kim, Sun-A Ahn, Seung-Gu Yeo, Jae Youl Cho, Kyung-Hee Kim and Seung Cheol Kim Source Type: research
FEDRR: fast, exhaustive detection of redundant hierarchical relations for quality improvement of large biomedical ontologies
Redundant hierarchical relations refer to such patterns as two paths from one concept to another, one with length one (direct) and the other with length greater than one (indirect). Each redundant relation rep... (Source: BioData Mining)
Source: BioData Mining - October 10, 2016 Category: Bioinformatics Authors: Guangming Xing, Guo-Qiang Zhang and Licong Cui Source Type: research
ProtNN: fast and accurate protein 3D-structure classification in structural and topological space
Studying the functions and structures of proteins is important for understanding the molecular mechanisms of life. The number of publicly available protein structures has increasingly become extremely large. S... (Source: BioData Mining)
Source: BioData Mining - September 23, 2016 Category: Bioinformatics Authors: Wajdi Dhifli and Abdoulaye Banir é Diallo Source Type: research
The tip of the iceberg: challenges of accessing hospital electronic health record data for biological data mining
Modern cohort studies include self-reported measures on disease, behavior and lifestyle, sensor-based observations from mobile phones and wearables, and rich -omics data. Follow-up is often achieved through el... (Source: BioData Mining)
Source: BioData Mining - September 22, 2016 Category: Bioinformatics Authors: Spiros C. Denaxas, Folkert W. Asselbergs and Jason H. Moore Source Type: research
Functional networks inference from rule-based machine learning models
Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the si... (Source: BioData Mining)
Source: BioData Mining - September 5, 2016 Category: Bioinformatics Authors: Nicola Lazzarini, Pawe ł, Widera, Stuart Williamson, Rakesh Heer, Natalio Krasnogor and Jaume Bacardit Source Type: research
A biologically informed method for detecting rare variant associations
BioBin is a bioinformatics software package developed to automate the process of binning rare variants into groups for statistical association analysis using a biological knowledge-driven framework. BioBin col... (Source: BioData Mining)
Source: BioData Mining - August 30, 2016 Category: Bioinformatics Authors: Carrie Colleen Buchanan Moore, Anna Okula Basile, John Robert Wallace, Alex Thomas Frase and Marylyn DeRiggi Ritchie Source Type: research
msBiodat analysis tool, big data analysis for high-throughput experiments
Mass spectrometry (MS) are a group of a high-throughput techniques used to increase knowledge about biomolecules. They produce a large amount of data which is presented as a list of hundreds or thousands of pr... (Source: BioData Mining)
Source: BioData Mining - August 19, 2016 Category: Bioinformatics Authors: Pau M. Mu ñoz-Torres, Filip Rokć, Robert Belužic, Ivana Grbeša and Oliver Vugrek Source Type: research
Mango: combining and analyzing heterogeneous biological networks
Heterogeneous biological data such as sequence matches, gene expression correlations, protein-protein interactions, and biochemical pathways can be merged and analyzed via graphs, or networks. Existing softwar... (Source: BioData Mining)
Source: BioData Mining - August 2, 2016 Category: Bioinformatics Authors: Jennifer Chang, Hyejin Cho and Hui-Hsien Chou Source Type: research
Joint analysis of multiple high-dimensional data types using sparse matrix approximations of rank-1 with applications to ovarian and liver cancer
Technological advances enable the cost-effective acquisition of Multi-Modal Data Sets (MMDS) composed of measurements for multiple, high-dimensional data types obtained from a common set of bio-samples. The joint... (Source: BioData Mining)
Source: BioData Mining - July 29, 2016 Category: Bioinformatics Authors: Gordon Okimoto, Ashkan Zeinalzadeh, Tom Wenska, Michael Loomis, James B. Nation, Tiphaine Fabre, Maarit Tiirikainen, Brenda Hernandez, Owen Chan, Linda Wong and Sandi Kwee Source Type: research
Representing and querying disease networks using graph databases
Systems biology experiments generate large volumes of data of multiple modalities and this information presents a challenge for integration due to a mix of complexity together with rich semantics. Here, we des... (Source: BioData Mining)
Source: BioData Mining - July 25, 2016 Category: Bioinformatics Authors: Artem Lysenko, Irina A. Roznov ăţ, Mansoor Saqi, Alexander Mazein, Christopher J Rawlings and Charles Auffray Source Type: research
Principal component analysis based unsupervised feature extraction applied to budding yeast temporally periodic gene expression
The recently proposed principal component analysis (PCA) based unsupervised feature extraction (FE) has successfully been applied to various bioinformatics problems ranging from biomarker identification to the... (Source: BioData Mining)
Source: BioData Mining - June 29, 2016 Category: Bioinformatics Authors: Y-h Taguchi Source Type: research
Data integration to prioritize drugs using genomics and curated data
Genomic alterations affecting drug target proteins occur in several tumor types and are prime candidates for patient-specific tailored treatments. Increasingly, patients likely to benefit from targeted cancer ... (Source: BioData Mining)
Source: BioData Mining - May 26, 2016 Category: Bioinformatics Authors: Riku Louhimo, Marko Laakso, Denis Belitskin, Juha Klefström, Rainer Lehtonen and Sampsa Hautaniemi Source Type: research
SePIA: RNA and small RNA sequence processing, integration, and analysis
Large-scale sequencing experiments are complex and require a wide spectrum of computational tools to extract and interpret relevant biological information. This is especially true in projects where individual ... (Source: BioData Mining)
Source: BioData Mining - May 20, 2016 Category: Bioinformatics Authors: Katherine Icay, Ping Chen, Alejandra Cervera, Ville Rantanen, Rainer Lehtonen and Sampsa Hautaniemi Source Type: research
Machine learning algorithms for mode-of-action classification in toxicity assessment
Real Time Cell Analysis (RTCA) technology is used to monitor cellular changes continuously over the entire exposure period. Combining with different testing concentrations, the profiles have potential in probi... (Source: BioData Mining)
Source: BioData Mining - May 13, 2016 Category: Bioinformatics Authors: Yile Zhang, Yau Shu Wong, Jian Deng, Cristina Anton, Stephan Gabos, Weiping Zhang, Dorothy Yu Huang and Can Jin Source Type: research
Identification of genetic interaction networks via an evolutionary algorithm evolved Bayesian network
The future of medicine is moving towards the phase of precision medicine, with the goal to prevent and treat diseases by taking inter-individual variability into account. A large part of the variability lies i... (Source: BioData Mining)
Source: BioData Mining - May 10, 2016 Category: Bioinformatics Authors: Ruowang Li, Scott M. Dudek, Dokyoon Kim, Molly A. Hall, Yuki Bradford, Peggy L. Peissig, Murray H. Brilliant, James G. Linneman, Catherine A. McCarty, Le Bao and Marylyn D. Ritchie Source Type: research
