The scoring of poses in protein-protein docking: current capabilities and future directions.

abstract：BACKGROUND:The UNO/RIC Nanopore Detector provides a new way to study the binding and conformational changes of individual antibodies. Many critical questions regarding antibody function are still unresolved, questions that can be approached in a new way with the nanopore detector. RESULTS:We present evidence that diff...

journal_title：BMC bioinformatics

authors： Winters-Hilt S,Morales E,Amin I,Stoyanov A

更新日期：2007-11-01 00:00:00

abstract：BACKGROUND:Failure on Highly Active Anti-Retroviral Treatment is often accompanied with development of antiviral resistance to one or more drugs included in the treatment. In general, the virus is more likely to develop resistance to drugs with a lower genetic barrier. Previously, we developed a method to reverse engin...

journal_title：BMC bioinformatics

authors： Theys K,Deforche K,Beheydt G,Moreau Y,van Laethem K,Lemey P,Camacho RJ,Rhee SY,Shafer RW,Van Wijngaerden E,Vandamme AM

更新日期：2010-08-03 00:00:00

abstract：BACKGROUND:In quantitative proteomics, peptide mapping is a valuable approach to combine positional quantitative information with topographical and domain information of proteins. Quantitative proteomic analysis of cell surface shedding is an exemplary application area of this approach. RESULTS:We developed ImproViser...

journal_title：BMC bioinformatics

authors： Videm P,Gunasekaran D,Schröder B,Mayer B,Biniossek ML,Schilling O

更新日期：2014-06-19 00:00:00

abstract：BACKGROUND:In real-time PCR data analysis, the cycle threshold (CT) method is currently the gold standard. This method is based on an assumption of equal PCR efficiency in all reactions, and precision may suffer if this condition is not met. Nonlinear regression analysis (NLR) or curve fitting has therefore been sugges...

journal_title：BMC bioinformatics

authors： Goll R,Olsen T,Cui G,Florholmen J

更新日期：2006-03-03 00:00:00

abstract：BACKGROUND:One approach to improving the personalized treatment of cancer is to understand the cellular signaling transduction pathways that cause cancer at the level of the individual patient. In this study, we used unsupervised deep learning to learn the hierarchical structure within cancer gene expression data. Deep...

journal_title：BMC bioinformatics

authors： Young JD,Cai C,Lu X

更新日期：2017-10-03 00:00:00

abstract：BACKGROUND:The classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning based approaches. Recently, the deep forest model has been proposed a...

journal_title：BMC bioinformatics

authors： Guo Y,Liu S,Li Z,Shang X

更新日期：2018-04-11 00:00:00

abstract：BACKGROUND:We develop a probabilistic model for combining kernel matrices to predict the function of proteins. It extends previous approaches in that it can handle multiple labels which naturally appear in the context of protein function. RESULTS:Explicit modeling of multilabels significantly improves the capability o...

journal_title：BMC bioinformatics

authors： Roth V,Fischer B

更新日期：2007-05-03 00:00:00

abstract：BACKGROUND:The low success rate and high cost of drug discovery requires the development of new paradigms to identify molecules of therapeutic value. The Anatomical Therapeutic Chemical (ATC) Code System is a World Health Organization (WHO) proposed classification that assigns multi-level codes to compounds based on th...

journal_title：BMC bioinformatics

authors： Olson T,Singh R

更新日期：2017-06-07 00:00:00

abstract：BACKGROUND:Next (second) generation sequencing is an increasingly important tool for many areas of molecular biology, however, care must be taken when interpreting its output. Even a low error rate can cause a large number of errors due to the high number of nucleotides being sequenced. Identifying sequencing errors fr...

journal_title：BMC bioinformatics

authors： Sleep JA,Schreiber AW,Baumann U

更新日期：2013-12-18 00:00:00

abstract：BACKGROUND:PacBio sequencing platform offers longer read lengths than the second-generation sequencing technologies. It has revolutionized de novo genome assembly and enabled the automated reconstruction of reference-quality genomes. Due to its extremely wide range of application areas, fast sequencing simulation syste...

journal_title：BMC bioinformatics

authors： Wei ZG,Zhang SW

更新日期：2018-05-22 00:00:00

abstract：BACKGROUND:Next Generation Sequencing techniques are producing enormous amounts of biological sequence data and analysis becomes a major computational problem. Currently, most analysis, especially the identification of conserved regions, relies heavily on Multiple Sequence Alignment and its various heuristics such as p...

journal_title：BMC bioinformatics

authors： Nagar A,Hahsler M

更新日期：2013-01-01 00:00:00

abstract：BACKGROUND:Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible for serious diseases, with a great scientific impact and a wide application area. Several standalone applications had been developed in order t...

journal_title：BMC bioinformatics

authors： Corradi L,Fato M,Porro I,Scaglione S,Torterolo L

更新日期：2008-11-13 00:00:00

abstract：BACKGROUND:MLPA method is a potentially useful semi-quantitative method to detect copy number alterations in targeted regions. In this paper, we propose a method for the normalization procedure based on a non-linear mixed-model, as well as a new approach for determining the statistical significance of altered probes ba...

journal_title：BMC bioinformatics

authors： González JR,Carrasco JL,Armengol L,Villatoro S,Jover L,Yasui Y,Estivill X

更新日期：2008-06-04 00:00:00

abstract：BACKGROUND:Genome scale data on protein interactions are generally represented as large networks, or graphs, where hundreds or thousands of proteins are linked to one another. Since proteins tend to function in groups, or complexes, an important goal has been to reliably identify protein complexes from these graphs. Th...

journal_title：BMC bioinformatics

authors： Vlasblom J,Wodak SJ

更新日期：2009-03-30 00:00:00

abstract：BACKGROUND:The nucleosome is the fundamental packing unit of DNAs in eukaryotic cells. Its detailed positioning on the genome is closely related to chromosome functions. Increasing evidence has shown that genomic DNA sequence itself is highly predictive of nucleosome positioning genome-wide. Therefore a fast software t...

journal_title：BMC bioinformatics

authors： Xi L,Fondufe-Mittendorf Y,Xia L,Flatow J,Widom J,Wang JP

更新日期：2010-06-24 00:00:00

abstract：BACKGROUND:Fluorescence microscopy is widely used to determine the subcellular location of proteins. Efforts to determine location on a proteome-wide basis create a need for automated methods to analyze the resulting images. Over the past ten years, the feasibility of using machine learning methods to recognize all maj...

journal_title：BMC bioinformatics

authors： Chebira A,Barbotin Y,Jackson C,Merryman T,Srinivasa G,Murphy RF,Kovacević J

更新日期：2007-06-19 00:00:00

abstract：BACKGROUND:The analysis of DNA copy number variants (CNV) has increasing impact in the field of genetic diagnostics and research. However, the interpretation of CNV data derived from high resolution array CGH or NGS platforms is complicated by the considerable variability of the human genome. Therefore, tools for multi...

journal_title：BMC bioinformatics

authors： Tebel K,Boldt V,Steininger A,Port M,Ebert G,Ullmann R

更新日期：2017-01-06 00:00:00

abstract：BACKGROUND:Manual chemical data curation from publications is error-prone, time consuming, and hard to maintain up-to-date data sets. Automatic information extraction can be used as a tool to reduce these problems. Since chemical structures usually described in images, information extraction needs to combine structure ...

journal_title：BMC bioinformatics

authors： Tharatipyakul A,Numnark S,Wichadakul D,Ingsriswang S

更新日期：2012-01-01 00:00:00

abstract：BACKGROUND:In recent years, to investigate challenging bioinformatics problems, the utilization of multiple genomic and proteomic sources has become immensely popular among researchers. One such issue is feature or gene selection and identifying relevant and non-redundant marker genes from high dimensional gene express...

journal_title：BMC bioinformatics

authors： Acharya S,Cui L,Pan Y

更新日期：2020-12-30 00:00:00

abstract：BACKGROUND:Over one hundred different types of post-transcriptional RNA modifications have been identified in human. Researchers discovered that RNA modifications can regulate various biological processes, and RNA methylation, especially N6-methyladenosine, has become one of the most researched topics in epigenetics. ...

journal_title：BMC bioinformatics

authors： Wu X,Wei Z,Chen K,Zhang Q,Su J,Liu H,Zhang L,Meng J

更新日期：2019-05-02 00:00:00

abstract：BACKGROUND:Viral infectious diseases are the serious threat for human health. The receptor-binding is the first step for the viral infection of hosts. To more effectively treat human viral infectious diseases, the hidden virus-receptor interactions must be discovered. However, current computational methods for predicti...

journal_title：BMC bioinformatics

authors： Yan C,Duan G,Wu FX,Wang J

更新日期：2019-12-27 00:00:00

abstract：BACKGROUND:One of the main goals in cancer studies including high-throughput microRNA (miRNA) and mRNA data is to find and assess prognostic signatures capable of predicting clinical outcome. Both mRNA and miRNA expression changes in cancer diseases are described to reflect clinical characteristics like staging and pro...

journal_title：BMC bioinformatics

authors： Gade S,Porzelius C,Fälth M,Brase JC,Wuttig D,Kuner R,Binder H,Sültmann H,Beissbarth T

更新日期：2011-12-21 00:00:00

abstract：BACKGROUND:Knowing the subcellular location of proteins provides clues to their function as well as the interconnectivity of biological processes. Dozens of tools are available for predicting protein location in the eukaryotic cell. Each tool performs well on certain data sets, but their predictions often disagree for ...

journal_title：BMC bioinformatics

authors： Shen YQ,Burger G

更新日期：2007-10-29 00:00:00

abstract：BACKGROUND:Machine learning has been utilized to predict cancer drug response from multi-omics data generated from sensitivities of cancer cell lines to different therapeutic compounds. Here, we build machine learning models using gene expression data from patients' primary tumor tissues to predict whether a patient wi...

journal_title：BMC bioinformatics

authors： Clayton EA,Pujol TA,McDonald JF,Qiu P

更新日期：2020-09-30 00:00:00

abstract：BACKGROUND:The large gap between the number of protein sequences in databases and the number of functionally characterized proteins calls for the development of a fast computational tool for the prediction of subnuclear and subcellular localizations generally applicable to protein sequences. The information on localiza...

journal_title：BMC bioinformatics

authors： Lei Z,Dai Y

更新日期：2005-12-07 00:00:00

abstract：BACKGROUND:A phylogeny postulates shared ancestry relationships among organisms in the form of a binary tree. Phylogenies attempt to answer an important question posed in biology: what are the ancestor-descendent relationships between organisms? At the core of every biological problem lies a phylogenetic component. The...

journal_title：BMC bioinformatics

authors： Varón A,Wheeler WC

更新日期：2013-02-26 00:00:00

abstract：BACKGROUND:Activation of naïve B lymphocytes by extracellular ligands, e.g. antigen, lipopolysaccharide (LPS) and CD40 ligand, induces a combination of common and ligand-specific phenotypic changes through complex signal transduction pathways. For example, although all three of these ligands induce proliferation, only ...

journal_title：BMC bioinformatics

authors： Lee JA,Sinkovits RS,Mock D,Rab EL,Cai J,Yang P,Saunders B,Hsueh RC,Choi S,Subramaniam S,Scheuermann RH,Alliance for Cellular Signaling.

更新日期：2006-05-02 00:00:00

abstract：BACKGROUND:Interpretation of quantitative metagenomics data is important for our understanding of ecosystem functioning and assessing differences between various environmental samples. There is a need for an easy to use tool to explore the often complex metagenomics data in taxonomic and functional context. RESULTS:He...

journal_title：BMC bioinformatics

authors： Sanli K,Karlsson FH,Nookaew I,Nielsen J

更新日期：2013-02-01 00:00:00

abstract：BACKGROUND:The amount of gene expression data available in public repositories has grown exponentially in the last years, now requiring new data mining tools to transform them in information easily accessible to biologists. RESULTS:By exploiting expression data publicly available in the Gene Expression Omnibus (GEO) d...

journal_title：BMC bioinformatics

authors： Cremaschi P,Rovida S,Sacchi L,Lisa A,Calvi F,Montecucco A,Biamonti G,Bione S,Sacchi G

更新日期：2014-01-01 00:00:00

abstract：BACKGROUND:High-throughput screens comparing growth rates of arrays of distinct micro-organism cultures on solid agar are useful, rapid methods of quantifying genetic interactions. Growth rate is an informative phenotype which can be estimated by measuring cell densities at one or more times after inoculation. Precise ...

journal_title：BMC bioinformatics

authors： Lawless C,Wilkinson DJ,Young A,Addinall SG,Lydall DA

更新日期：2010-05-28 00:00:00