Comparison of scoring systems for invasive pests using ROC analysis and Monte Carlo simulation

Different international plant protection organisations advocate different schemes for conducting pest risk assessments. Most of these schemes use structured questionnaire in which experts are asked to score several items using an ordinal scale. The scores are then combined using a range of procedures, such as simple arithmetic mean, weighted averages, multiplication of scores, and cumulative sums. The most useful schemes will correctly identify harmful pests and identify ones that are not. As the quality of a pest risk assessment can depend on the characteristics of the scoring system used by the risk assessors (i.e., on the number of points of the scale and on the method used for combining the component scores), it is important to assess and compare the performance of different scoring systems. In this article, we proposed a new method for assessing scoring systems. Its principle is to simulate virtual data using a stochastic model and, then, to estimate sensitivity and specificity values from these data for different scoring systems. The interest of our approach was illustrated in a case study where several scoring systems were compared. Data for this analysis were generated using a probabilistic model describing the pest introduction process. The generated data were then used to simulate the outcome of scoring systems and to assess the accuracy of the decisions about positive and negative introduction. The results showed that ordinal scales with at most 5 or 6 points were sufficient and that the multiplication-based scoring systems performed better than their sum-based counterparts. The proposed method could be used in the future to assess a great diversity of scoring systems.

Regresión logística y curvas roc

p.181-182

Distributions d'auto-amorçage exactes ponctuelles des courbes ROC et des courbes de coûts

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Análisis ROC y z-ROC en memoria de reconocimiento : modelos continuos, de umbral y asimétricos.

Resumen tomado de la publicación

ROC parameters in item and context recognition. 'Par??metros ROC en el reconocimiento de items y contextos'

Resumen tomado de la publicaci??n. Resumen tambi??n en ingl??s

Estudio del rendimiento académico universitario basado en curvas ROC.

Se estudia el rendimiento académico universitario de los alumnos a través de las calificaciones de entrada a la Universidad. En particular, centrado en las licenciaturas de Economía (LE) y Administración y Dirección de Empresas (LADE) de la Universidad de Murcia, utilizando como medida del rendimiento académico de los alumnos asignaturas de matemáticas de dichas titulaciones. Para ello, se realiza el análisis de los datos mediante la técnica estadística curva ROC (Receiver Operating Characteristic); este método proporciona una medida que permite discriminar entre alumnos que obtienen un buen rendimiento académico y uno malo, así como comparar distintos parámetros de clasificación de dicho rendimiento .

Variables TIC vinculadas a la generación de nuevos escenarios de aprendizaje en la enseñanza universitaria : aportes de las curvas ROC para el análisis de diferencias

Resumen tomado de la publicación

Eficiencia de la detección automática de potenciales evocados auditivos de estado estable a múltiples frecuencias evaluada mediante la metodología ROC.

Resumen en inglés. Resumen tomado de la publicación

C??mo construir un roc??dromo de escalada

Resumen tomado de la publicaci??n

Jaciment prehistòric del «Roc de la Melca» i la seva cronologia: Sant Aniol de Finestres (Girona)

Descripció del jaciment arqueològic del 'Roc de la Melca', en la vall de Sant Aniol de Finestres (Girona). Es descriuen la indústria lítica i els problemes que presenta la cronologia del 'Roc de la Melca'

GTP binding and intramolecular regulation by the ROC domain of Death Associated Protein Kinase 1

The ROCO proteins are a family of large, multidomain proteins characterised by the presence of a Ras of complex proteins (ROC) domain followed by a COR, or C-terminal of ROC, domain. It has previously been shown that the ROC domain of the human ROCO protein Leucine Rich Repeat Kinase 2 (LRRK2) controls its kinase activity. Here, the ability of the ROC domain of another human ROCO protein, Death Associated Protein Kinase 1 (DAPK1), to bind GTP and control its kinase activity has been evaluated. In contrast to LRRK2, loss of GTP binding by DAPK1 does not result in loss of kinase activity, instead acting to modulate this activity. These data highlight the ROC domain of DAPK1 as a target for modifiers of this proteins function, and casts light on the role of ROC domains as intramolecular regulators in complex proteins with implications for a broad range of human diseases.

Structure of the ROC domain from the Parkinson's disease-associated leucine-rich repeat kinase 2 reveals a dimeric GTPase

Mutations in leucine-rich repeat kinase 2 (LRRK2) are the most common cause of Parkinson's disease (PD). LRRK2 contains a Ras of complex proteins (ROC) domain that may act as a GTPase to regulate its protein kinase activity. The structure of ROC and the mechanism(s) by which it regulates kinase activity are not known. Here, we report the crystal structure of the LRRK2 ROC domain in complex with GDP-Mg2+ at 2.0-Å resolution. The structure displays a dimeric fold generated by extensive domain-swapping, resulting in a pair of active sites constructed with essential functional groups contributed from both monomers. Two PD-associated pathogenic residues, R1441 and I1371, are located at the interface of two monomers and provide exquisite interactions to stabilize the ROC dimer. The structure demonstrates that loss of stabilizing forces in the ROC dimer is likely related to decreased GTPase activity resulting from mutations at these sites. Our data suggest that the ROC domain may regulate LRRK2 kinase activity as a dimer, possibly via the C-terminal of ROC (COR) domain as a molecular hinge. The structure of the LRRK2 ROC domain also represents a signature from a previously undescribed class of GTPases from complex proteins and results may provide a unique molecular target for therapeutics in PD.