UPS 2.0: unique probe selector for probe design and oligonucleotide microarrays at the pangenomic/ genomic level

<p>Abstract</p> <p>Background</p> <p>Nucleic acid hybridization is an extensively adopted principle in biomedical research, in which the performance of any hybridization-based method depends on the specificity of probes to their targets. To determine the optimal probe(s) for detecting target(s) from a sample cocktail, we developed a novel algorithm, which has been implemented into a web platform for probe designing. This probe design workflow is now upgraded to satisfy experiments that require a probe designing tool to take the increasing volume of sequence datasets.</p> <p>Results</p> <p>Algorithms and probe parameters applied in UPS 2.0 include GC content, the secondary structure, melting temperature (Tm), the stability of the probe-target duplex estimated by the thermodynamic model, sequence complexity, similarity of probes to non-target sequences, and other empirical parameters used in the laboratory. Several probe background options,<b><it>Unique probe within a group</it></b><it>,</it><b><it>Unique probe in a specific Unigene set</it></b><it>,</it><b><it>Unique probe based onthe pangenomic level</it></b><it>,</it> and <b><it>Unique Probe in the user-defined genome/transcriptome</it></b><it>,</it> are available to meet the scenarios that the experiments will be conducted. Parameters, such as salt concentration and the lower-bound Tm of probes, are available for users to optimize their probe design query. Output files are available for download on the result page. Probes designed by the UPS algorithm are suitable for generating microarrays, and the performance of UPS-designed probes has been validated by experiments.</p> <p>Conclusions</p> <p>The UPS 2.0 evaluates probe-to-target hybridization under a user-defined condition to ensure high-performance hybridization with minimal chance of non-specific binding at the pangenomic and genomic levels. The UPS algorithm mimics the target/non-target mixture in an experiment and is very useful in developing diagnostic kits and microarrays. The UPS 2.0 website has had more than 1,300 visits and 360,000 sequences performed the probe designing task in the last 30 months. It is freely accessible at <url>http://array.iis.sinica.edu.tw/ups/.</url></p> <p>Screen cast: <url>http://array.iis.sinica.edu.tw/ups/demo/demo.htm</url></p

PALM: A Paralleled and Integrated Framework for Phylogenetic Inference with Automatic Likelihood Model Selectors

BACKGROUND: Selecting an appropriate substitution model and deriving a tree topology for a given sequence set are essential in phylogenetic analysis. However, such time consuming, computationally intensive tasks rely on knowledge of substitution model theories and related expertise to run through all possible combinations of several separate programs. To ensure a thorough and efficient analysis and avert tedious manipulations of various programs, this work presents an intuitive framework, the phylogenetic reconstruction with automatic likelihood model selectors (PALM), with convincing, updated algorithms and a best-fit model selection mechanism for seamless phylogenetic analysis. METHODOLOGY: As an integrated framework of ClustalW, PhyML, MODELTEST, ProtTest, and several in-house programs, PALM evaluates the fitness of 56 substitution models for nucleotide sequences and 112 substitution models for protein sequences with scores in various criteria. The input for PALM can be either sequences in FASTA format or a sequence alignment file in PHYLIP format. To accelerate the computing of maximum likelihood and bootstrapping, this work integrates MPICH2/PhyML, PalmMonitor and Palm job controller across several machines with multiple processors and adopts the task parallelism approach. Moreover, an intuitive and interactive web component, PalmTree, is developed for displaying and operating the output tree with options of tree rooting, branches swapping, viewing the branch length values, and viewing bootstrapping score, as well as removing nodes to restart analysis iteratively. SIGNIFICANCE: The workflow of PALM is straightforward and coherent. Via a succinct, user-friendly interface, researchers unfamiliar with phylogenetic analysis can easily use this server to submit sequences, retrieve the output, and re-submit a job based on a previous result if some sequences are to be deleted or added for phylogenetic reconstruction. PALM results in an inference of phylogenetic relationship not only by vanquishing the computation difficulty of ML methods but also providing statistic methods for model selection and bootstrapping. The proposed approach can reduce calculation time, which is particularly relevant when querying a large data set. PALM can be accessed online at http://palm.iis.sinica.edu.tw

Inverse Melting of an Electronic Liquid Crystal

Inverse melting refers to the rare thermodynamic phenomenon in which a solid melts into a liquid upon cooling, a transition that can occur only when the ordered (solid) phase has more entropy than the disordered (liquid) phase, and that has so far only been observed in a handful of systems. Here we report the first experimental observation for the inverse melting of an electronic liquid crystalline order in strontium-doped lanthanum nickelate, a compound isostructural with the superconducting cuprates, with a hole doping concentration of 1/3. Using x-ray scattering, we demonstrate that the isotropic charge modulation is driven to nematic order by fluctuating spins and shows an inverse melting transition. Using a phenomenological Landau theory, we show that this inverse melting transition is due to the interlayer coupling between the charge and spin orders. This discovery points to the importance of the interlayer correlations in the system, and provides a new perspective to study the intricate nature of the electronic liquid crystal phases in strongly correlated electronic systems, including possibly the Cu- and Fe-based high-Tc superconductors.Comment: 7 pages, 7 figure

Inverse order-disorder transition of charge stripes

We report an unusual transition behavior of charge stripes in La1.67Sr0.33NiO4 using x-ray scattering. The segregated holes in La1.67Sr0.33NiO4 are observed to form anisotropic stripes in the a × b plane of the crystal space below the transition temperature T 238 K, and at the same time, display an unusual inverse order-disorder transition along the c axis. Using a phenomenological Landau theory, we show that this inverse transition is due to the interlayer coupling between the charge and spin orders. This discovery points to the importance of the interlayer correlations in the strongly correlated electrons system

Engineering the shape and structure of materials by fractal cut

In this paper we discuss the transformation of a sheet of material into a wide range of desired shapes and patterns by introducing a set of simple cuts in a multilevel hierarchy with different motifs. Each choice of hierarchical cut motif and cut level allows the material to expand into a unique structure with a unique set of properties. We can reverse-engineer the desired expanded geometries to find the requisite cut pattern to produce it without changing the physical properties of the initial material. The concept was experimentally realized and applied to create an electrode that expands to >800% the original area with only very minor stretching of the underlying material. The generality of our approach greatly expands the design space for materials so that they can be tuned for diverse applications.Korea Institute of Science and Technology (Internal Research Funding Grant 2Z04050)Korea Institute of Science and Technology (Internal Research Funding Grant 2V03320)National Research Council of Science and Technology (Grant NST-Yunghap-13-1)National Science Foundation (U.S.). Division of Materials Research (Grant 1120901)National Science Foundation (U.S.). Chemical, Bioengineering, Environmental, and Transport Systems (Grant 1240696

Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer’s disease

Abstract: Subjective cognitive decline (SCD) is regarded as the first clinical manifestation in the Alzheimer’s disease (AD) continuum. Investigating populations with SCD is important for understanding the early pathological mechanisms of AD and identifying SCD-related biomarkers, which are critical for the early detection of AD. With the advent of advanced neuroimaging techniques, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), accumulating evidence has revealed structural and functional brain alterations related to the symptoms of SCD. In this review, we summarize the main imaging features and key findings regarding SCD related to AD, from local and regional data to connectivity-based imaging measures, with the aim of delineating a multimodal imaging signature of SCD due to AD. Additionally, the interaction of SCD with other risk factors for dementia due to AD, such as age and the Apolipoprotein E (ApoE) ɛ4 status, has also been described. Finally, the possible explanations for the inconsistent and heterogeneous neuroimaging findings observed in individuals with SCD are discussed, along with future directions. Overall, the literature reveals a preferential vulnerability of AD signature regions in SCD in the context of AD, supporting the notion that individuals with SCD share a similar pattern of brain alterations with patients with mild cognitive impairment (MCI) and dementia due to AD. We conclude that these neuroimaging techniques, particularly multimodal neuroimaging techniques, have great potential for identifying the underlying pathological alterations associated with SCD. More longitudinal studies with larger sample sizes combined with more advanced imaging modeling approaches such as artificial intelligence are still warranted to establish their clinical utility