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Pablo Zentilli

dblp:49/362 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 75% Computational science and engineering · 25%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
drug discovery
0.122007
An efficient method for the detection and elimination of systematic error in high-throughput screening · Bioinform. 2007
HTS-Corrector: software for the statistical analysis and correction of experimental high-throughput screening data · Bioinform. 2006
Bioinformatics and computational biology › drug discovery
high-throughput screening
0.122007
An efficient method for the detection and elimination of systematic error in high-throughput screening · Bioinform. 2007
HTS-Corrector: software for the statistical analysis and correction of experimental high-throughput screening data · Bioinform. 2006
Bioinformatics and computational biology › drug discovery › high-throughput screening
hit selection
0.122007
An efficient method for the detection and elimination of systematic error in high-throughput screening · Bioinform. 2007
HTS-Corrector: software for the statistical analysis and correction of experimental high-throughput screening data · Bioinform. 2006
Computational science and engineering
systematic error correction
0.122007
An efficient method for the detection and elimination of systematic error in high-throughput screening · Bioinform. 2007
HTS-Corrector: software for the statistical analysis and correction of experimental high-throughput screening data · Bioinform. 2006

Methods — techniques the papers use, named apart from their topics

simulation · 0.1well correction · 0.1hit-sigma distribution · 0.1background evaluation · 0.1
YearPublicationVenuePosition
2007 Introducing students to professional software construction: a "software construction and maintenance" course and its maintenance corpus
abstract
It is widely accepted that there is more to software construction than basic programming skills. Professional software construction involves not only understanding some theoretical concepts, but also mastering appropriate tools and practices. In this paper, we present an undergraduate course in Software Construction and Maintenance, developed with the goal of introducing students to those key concepts, tools and practices.
Guy Tremblay, Bruno Malenfant, Aziz Salah, Pablo Zentilli
ITiCSE4
2007 An efficient method for the detection and elimination of systematic error in high-throughput screening
abstract
MOTIVATION: High-throughput screening (HTS) is an early-stage process in drug discovery which allows thousands of chemical compounds to be tested in a single study. We report a method for correcting HTS data prior to the hit selection process (i.e. selection of active compounds). The proposed correction minimizes the impact of systematic errors which may affect the hit selection in HTS. The introduced method, called a well correction, proceeds by correcting the distribution of measurements within wells of a given HTS assay. We use simulated and experimental data to illustrate the advantages of the new method compared to other widely-used methods of data correction and hit selection in HTS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Vladimir Makarenkov, Pablo Zentilli, Dmytro Kevorkov, Andrei V. Gagarin, Nathalie Malo, Robert Nadon
Bioinform.2
2006 HTS-Corrector: software for the statistical analysis and correction of experimental high-throughput screening data
abstract
MOTIVATION: High-throughput screening (HTS) plays a central role in modern drug discovery, allowing for testing of >100,000 compounds per screen. The aim of our work was to develop and implement methods for minimizing the impact of systematic error in the analysis of HTS data. To the best of our knowledge, two new data correction methods included in HTS-Corrector are not available in any existing commercial software or freeware. RESULTS: This paper describes HTS-Corrector, a software application for the analysis of HTS data, detection and visualization of systematic error, and corresponding correction of HTS signals. Three new methods for the statistical analysis and correction of raw HTS data are included in HTS-Corrector: background evaluation, well correction and hit-sigma distribution procedures intended to minimize the impact of systematic errors. We discuss the main features of HTS-Corrector and demonstrate the benefits of the algorithms.
Vladimir Makarenkov, Dmytro Kevorkov, Pablo Zentilli, Andrei V. Gagarin, Nathalie Malo, Robert Nadon
Bioinform.3