Determining the Success of NCAA Basketball Teams through Team Characteristics

Every year much of the nation becomes engulfed in the NCAA basketball postseason tournament more affectionately known as “March Madness.” The tournament has received the name because of the ability for any team to win a single game and advance to the next round. The purpose of this study is to determine whether concrete statistical measures can be used to predict the final outcome of the tournament. The data collected in the study include 13 independent variables ranging from the 2003-2004 season up until the current 2009-2010 season. Different tests were run in an attempt to achieve the most accurate predictive model. First, the data were input into Excel and ordinary least squares regressions were run for each year. Then the data were compiled into one file and an ordinary least squares regression was run on that collection of data in Excel. Next, the data were input into Minitab and a stepwise regression was run in order to keep only the significant independent variables. Following that, a regression analysis was run in Minitab. The coefficients from that regression analysis were input into a file with the 2009-2010 data in an attempt to test the model’s results against the actual results. All of the models developed, except one for the year 2005-2006, were determined to be significant. There were 6 significant independent variables determined. The final results showed that although the model developed through the study was significant, the ability to accurately predict the outcomes is very difficult

Practical Aspects of microRNA Target Prediction

microRNAs (miRNAs) are endogenous non-coding RNAs that control gene expression at the posttranscriptional level. These small regulatory molecules play a key role in the majority of biological processes and their expression is also tightly regulated. Both the deregulation of genes controlled by miRNAs and the altered miRNA expression have been linked to many disorders, including cancer, cardiovascular, metabolic and neurodegenerative diseases. Therefore, it is of particular interest to reliably predict potential miRNA targets which might be involved in these diseases. However, interactions between miRNAs and their targets are complex and very often there are numerous putative miRNA recognition sites in mRNAs. Many miRNA targets have been computationally predicted but only a limited number of these were experimentally validated. Although a variety of miRNA target prediction algorithms are available, results of their application are often inconsistent. Hence, finding a functional miRNA target is still a challenging task. In this review, currently available and frequently used computational tools for miRNA target prediction, i.e., PicTar, TargetScan, DIANA-microT, miRanda, rna22 and PITA are outlined and various practical aspects of miRNA target analysis are extensively discussed. Moreover, the performance of three algorithms (PicTar, TargetScan and DIANA-microT) is both demonstrated and evaluated by performing an in-depth analysis of miRNA interactions with mRNAs derived from genes triggering hereditary neurological disorders known as trinucleotide repeat expansion diseases (TREDs), such as Huntington’s disease (HD), a number of spinocerebellar ataxias (SCAs), and myotonic dystrophy type 1 (DM1)

One Decade of Development and Evolution of MicroRNA Target Prediction Algorithms

Nearly two decades have passed since the publication of the first study reporting the discovery of microRNAs (miRNAs). The key role of miRNAs in post-transcriptional gene regulation led to the performance of an increasing number of studies focusing on origins, mechanisms of action and functionality of miRNAs. In order to associate each miRNA to a specific functionality it is essential to unveil the rules that govern miRNA action. Despite the fact that there has been significant improvement exposing structural characteristics of the miRNA-mRNA interaction, the entire physical mechanism is not yet fully understood. In this respect, the development of computational algorithms for miRNA target prediction becomes increasingly important. This manuscript summarizes the research done on miRNA target prediction. It describes the experimental data currently available and used in the field and presents three lines of computational approaches for target prediction. Finally, the authors put forward a number of considerations regarding current challenges and future direction

MicroRNA-9 controls dendritic development by targeting REST

MicroRNAs (miRNAs) are conserved noncoding RNAs that function as posttranscriptional regulators of gene expression. miR-9 is one of the most abundant miRNAs in the brain. Although the function of miR-9 has been well characterized in neural progenitors, its role in dendritic and synaptic development remains largely unknown. In order to target miR-9 in vivo, we developed a transgenic miRNA sponge mouse line allowing conditional inactivation of the miR-9 family in a spatio-temporal-controlled manner. Using this novel approach, we found that miR-9 controls dendritic growth and synaptic transmission in vivo. Furthermore, we demonstrate that miR-9-mediated downregulation of the transcriptional repressor REST is essential for proper dendritic growth.Fil: Giusti, Sebastian Alejandro. Max Planck Institute of Psychiatry; AlemaniaFil: Vogl, Annette M.. Max Planck Institute of Psychiatry; AlemaniaFil: Brockmann, Marina M.. Max Planck Institute of Psychiatry; AlemaniaFil: Vercelli, Claudia Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; ArgentinaFil: Rein, Martin L.. Max Planck Institute of Psychiatry; AlemaniaFil: Trümbach, Dietrich. Helmholtz Zentrum München; AlemaniaFil: Wurst, Wolfgang. Helmholtz Zentrum München; AlemaniaFil: Cazalla, Demian. University of Utah; Estados UnidosFil: Stein, Valentin. Universitaet Bonn; AlemaniaFil: Deussing, Jan M.. Max Planck Institute of Psychiatry; AlemaniaFil: Refojo, Damian. Max Planck Institute of Psychiatry; Alemani

GORAB scaffolds COPI at the trans-Golgi for efficient enzyme recycling and correct protein glycosylation

COPI is a key mediator of protein trafficking within the secretory pathway. COPI is recruited to the membrane primarily through binding to Arf GTPases, upon which it undergoes assembly to form coated transport intermediates responsible for trafficking numerous proteins, including Golgi-resident enzymes. Here, we identify GORAB, the protein mutated in the skin and bone disorder gerodermia osteodysplastica, as a component of the COPI machinery. GORAB forms stable domains at the trans-Golgi that, via interactions with the COPI-binding protein Scyl1, promote COPI recruitment to these domains. Pathogenic GORAB mutations perturb Scyl1 binding or GORAB assembly into domains, indicating the importance of these interactions. Loss of GORAB causes impairment of COPI-mediated retrieval of trans-Golgi enzymes, resulting in a deficit in glycosylation of secretory cargo proteins. Our results therefore identify GORAB as a COPI scaffolding factor, and support the view that defective protein glycosylation is a major disease mechanism in gerodermia osteodysplastica.Peer reviewe

Impaired proteoglycan glycosylation, elevated TGF-β signaling, and abnormal osteoblast differentiation as the basis for bone fragility in a mouse model for gerodermia osteodysplastica

<div><p>Gerodermia osteodysplastica (GO) is characterized by skin laxity and early-onset osteoporosis. <i>GORAB</i>, the responsible disease gene, encodes a small Golgi protein of poorly characterized function. To circumvent neonatal lethality of the <i>Gorab</i>^<i>Null</i> full knockout, <i>Gorab</i> was conditionally inactivated in mesenchymal progenitor cells (Prx1-cre), pre-osteoblasts (Runx2-cre), and late osteoblasts/osteocytes (Dmp1-cre), respectively. While in all three lines a reduction in trabecular bone density was evident, only <i>Gorab</i>^Prx1 and <i>Gorab</i>^Runx2 mutants showed dramatically thinned, porous cortical bone and spontaneous fractures. Collagen fibrils in the skin of <i>Gorab</i>^<i>Null</i> mutants and in bone of <i>Gorab</i>^Prx1 mutants were disorganized, which was also seen in a bone biopsy from a GO patient. Measurement of glycosaminoglycan contents revealed a reduction of dermatan sulfate levels in skin and cartilage from <i>Gorab</i>^<i>Null</i> mutants. In bone from <i>Gorab</i>^Prx1 mutants total glycosaminoglycan levels and the relative percentage of dermatan sulfate were both strongly diminished. Accordingly, the proteoglycans biglycan and decorin showed reduced glycanation. Also in cultured <i>GORAB</i>-deficient fibroblasts reduced decorin glycanation was evident. The Golgi compartment of these cells showed an accumulation of decorin, but reduced signals for dermatan sulfate. Moreover, we found elevated activation of TGF-β in <i>Gorab</i>^Prx1 bone tissue leading to enhanced downstream signalling, which was reproduced in <i>GORAB</i>-deficient fibroblasts. Our data suggest that the loss of <i>Gorab</i> primarily perturbs pre-osteoblasts. GO may be regarded as a congenital disorder of glycosylation affecting proteoglycan synthesis due to delayed transport and impaired posttranslational modification in the Golgi compartment.</p></div

Bridging the Gap between Glycosylation and Vesicle Traffic

Glycosylation is recognized as a vitally important posttranslational modification. The structure of glycans that decorate proteins and lipids is largely dictated by biosynthetic reactions occurring in the Golgi apparatus. This biosynthesis relies on the relative distribution of glycosyltransferases and glycosidases, which is maintained by retrograde vesicle traffic between Golgi cisternae. Tethering of vesicles at the Golgi apparatus prior to fusion is regulated by Rab GTPases, coiled-coil tethers termed golgins and the multisubunit tethering complex known as the conserved oligomeric Golgi (COG) complex. In this review we discuss the mechanisms involved in vesicle tethering at the Golgi apparatus and highlight the importance of tethering in the context of glycan biosynthesis and a set of diseases known as congenital disorders of glycosylation

RFMirTarget: A Random Forest Classifier for Human miRNA Target Gene Prediction

Abstract. MicroRNAs (miRNAs) are key regulators of eukaryotic gene expression whose fundamental role has been already identified in many cell pathways. The correct identification of miRNAs targets is a major challenge in bioinformatics. So far, machine learning-based methods for miRNA-target prediction have shown the best results in terms of specificity and sensitivity. However, despite its well-known efficiency in other classifying tasks, the random forest algorithm has not been employed in this problem. Therefore, in this work we present RFMirTarget, an efficient random forest miRNA-target prediction system. Our tool analyzes the alignment between a candidate miRNA-target pair and extracts a set of structural, thermodynamics, alignment and position-based features. Experiments have shown that RFMirTarget achieves a Matthew’s correlation coefficient nearly 48 % greater than the performance reported for the MultiMiTar, which was trained upon the same data set. In addition, tests performed with RFMirTarget reinforce the importance of the seed region for target prediction accuracy

Hypomorphic mutations of TRIP11 cause odontochondrodysplasia

Odontochondrodysplasia (ODCD) is an unresolved genetic disorder of skeletal and dental development. Here, we show that ODCD is caused by hypomorphic TRIP11 mutations, and we identify ODCD as the nonlethal counterpart to achondrogenesis 1A (ACG1A), the known null phenotype in humans. TRIP11 encodes Golgi-associated microtubule-binding protein 210 (GMAP-210), an essential tether protein of the Golgi apparatus that physically interacts with intraflagellar transport 20 (IFT20), a component of the ciliary intraflagellar transport complex B. This association and extraskeletal disease manifestations in ODCD point to a cilium-dependent pathogenesis. However, our functional studies in patient-derived primary cells clearly support a Golgi-based disease mechanism. In spite of reduced abundance, residual GMAP variants maintain partial Golgi integrity, normal global protein secretion, and subcellular distribution of IFT20 in ODCD. These functions are lost when GMAP-210 is completely abrogated in ACG1A. However, a similar defect in chondrocyte maturation is observed in both disorders, which produces a cellular achondrogenesis phenotype of different severity, ensuing from aberrant glycan processing and impaired extracellular matrix proteoglycan secretion by the Golgi apparatus