Systematic hybrid LOH: a new method to reduce false positives and negatives during screening of yeast gene deletion libraries

Yeast ◽  
2006 ◽  
Vol 23 (14-15) ◽  
pp. 1097-1106 ◽  
Author(s):  
David Alvaro ◽  
Ivana Sunjevaric ◽  
Robert J. D. Reid ◽  
Michael Lisby ◽  
David J. Stillman ◽  
...  
Keyword(s):  
Gene Deletion ◽  
False Positives ◽  
New Method ◽  
Yeast Gene ◽  
False Positives And Negatives ◽  
Deletion Libraries

scholarly journals False Positives and Negatives from Real Traffic with Intrusion Detection/Prevention Systems

2012 ◽  
pp. 87-90 ◽  
Author(s):  
Cheng-Yuan Ho ◽  
Ying-Dar Lin ◽  
Yuan-Cheng Lai ◽  
I-Wei Chen ◽  
Fu-Yu Wang ◽  
...  
Keyword(s):  
Intrusion Detection ◽  
False Positives ◽  
Real Traffic ◽  
False Positives And Negatives

DETECTION OF NEW COPIES OF SINE IN THE RICE GENOME

2020 ◽  
pp. 267-269
Author(s):  
A. Kamionskaya ◽  
E. Korotkov
Keyword(s):  
Rice Genome ◽  
False Positives ◽  
New Method ◽  
The Matrix

We represent here a new method for the detection of new copies of SINE elements. The method is based on the correlation of pairs of symbols. The correlation is used for the construction of a position-specific matrix as well as for the search of new repeat copies using the matrix. This allows us to enlarge the alphabet and to increase the sensitivity of the method. The method was used to study the rice genome. As a result, new copies of SINE repeats that were not included in the standard annotation were found. The number of false positives was evaluated.

scholarly journals A method for estimating existence of pairwise STM transaction conflicts

2018 ◽  
Vol 232 ◽  
pp. 04037
Author(s):  
Miroslav Popovic ◽  
Branislav Kordic ◽  
Marko Popovic ◽  
Ilija Basicevic
Keyword(s):  
System Performance ◽  
Time Complexity ◽  
Scheduling Algorithms ◽  
False Positives ◽  
New Method ◽  
False Negatives ◽  
Transaction Scheduling ◽  
Data Races ◽  
Cost Of Time ◽  
The Cost

STM transaction schedulers were introduced to improve system performance. However, designing online transaction scheduling algorithms is challenging because at the same time they should: (i) introduce minimal scheduling overhead, (ii) minimize the resulting makespan, and (iii) minimize contention in the resulting schedule. In our previous work we developed the online transaction scheduler architecture and the four scheduling algorithms, named RR, ETLB, AC, and AAC (listed in increasing order of their quality), for scheduling transactions on the Python STM. Both AC and AAC use Bernstein conditions to check for pairwise data races between transactions, at the cost of time complexity that is proportional to the product of the sizes of transaction’s read and write sets, which may be significant. In this paper we propose a method for estimating existence of pairwise transaction conflicts whose time complexity is Θ(1). We validate this method by analysing the resulting transaction schedules for the three benchmark workloads, named RDW, CFW, and WDW. The result of this analysis is positive and encouraging – AAC using the new method produces the same result as when using Bernstein conditions. The limitation of the new method is that it may have false reports, both false negatives and false positives.

scholarly journals mRNA with Mammalian Codon Bias Accumulates in Yeast Mutants with Constitutive Stress Granules

2020 ◽  
Vol 21 (4) ◽  
pp. 1234
Author(s):  
Natalia V. Kozlova ◽  
Chantal Pichon ◽  
A. Rachid Rahmouni
Keyword(s):  
Codon Bias ◽  
Gene Deletion ◽  
Stress Granules ◽  
Stress Factors ◽  
Yeast Gene ◽  
P Bodies ◽  
Mrna Surveillance ◽  
Steady State Levels ◽  
Cytoplasmic Structures ◽  
Yeast Mutants

Stress granules and P bodies are cytoplasmic structures assembled in response to various stress factors and represent sites of temporary storage or decay of mRNAs. Depending on the source of stress, the formation of these structures may be driven by distinct mechanisms, but several stresses have been shown to stabilize mRNAs via inhibition of deadenylation. A recent study identified yeast gene deletion mutants with constitutive stress granules and elevated P bodies; however, the mechanisms which trigger its formation remain poorly understood. Here, we investigate the possibility of accumulating mRNA with mammalian codon bias, which we termed the model RNA, in these mutants. We found that the model RNA accumulates in dcp2 and xrn1 mutants and in four mutants with constitutive stress granules overlapping with P bodies. However, in eight other mutants with constitutive stress granules, the model RNA is downregulated, or its steady state levels vary. We further suggest that the accumulation of the model RNA is linked to its protection from the main mRNA surveillance path. However, there is no obvious targeting of the model RNA to stress granules or P bodies. Thus, accumulation of the model RNA and formation of constitutive stress granules occur independently and only some paths inducing formation of constitutive stress granules will stabilize mRNA as well.

The study of protein–protein interactions in bacteria

2012 ◽  
Vol 58 (11) ◽  
pp. 1241-1257 ◽  
Author(s):  
Roberto Velasco-García ◽  
Rocío Vargas-Martínez
Keyword(s):  
Hybrid System ◽  
High Throughput ◽  
Protein Interactions ◽  
Specific Protein ◽  
False Positives ◽  
Interaction Networks ◽  
Protein Protein Interactions ◽  
Extensive Data ◽  
False Positives And Negatives

Many of the functions fulfilled by proteins in the cell require specific protein–protein interactions (PPI). During the last decade, the use of high-throughput experimental technologies, primarily based on the yeast 2-hybrid system, generated extensive data currently located in public databases. This information has been used to build interaction networks for different species. Unfortunately, due to the nature of the yeast 2-hybrid system, these databases contain many false positives and negatives, thus they require purging. A method for confirming these PPI is to test them using a technique that operates in vivo and detects binary PPI. This article comprises an overview of the study of PPI and describes the main techniques that have been used to identify bacterial PPI, prioritizing those that can be used for their verification, and it also mentions a number of PPI that have been identified or confirmed using these methods.

scholarly journals On minimizing assignment errors and the trade-off between false positives and negatives in parentage analysis

2013 ◽  
Vol 22 (23) ◽  
pp. 5738-5742 ◽  
Author(s):  
Hugo B. Harrison ◽  
Pablo Saenz-Agudelo ◽  
Serge Planes ◽  
Geoffrey P. Jones ◽  
Michael L. Berumen
Keyword(s):  
Parentage Analysis ◽  
False Positives ◽  
Trade Off ◽  
False Positives And Negatives

scholarly journals Model-driven analysis of experimentally determined growth phenotypes for 465 yeast gene deletion mutants under 16 different conditions

2008 ◽  
Vol 9 (9) ◽  
pp. R140 ◽  
Author(s):  
Evan S Snitkin ◽  
Aimée M Dudley ◽  
Daniel M Janse ◽  
Kaisheen Wong ◽  
George M Church ◽  
...  
Keyword(s):  
Gene Deletion ◽  
Deletion Mutants ◽  
Yeast Gene ◽  
Model Driven

scholarly journals Go-Around Detection Using Crowd-Sourced ADS-B Position Data

Aerospace ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. 16 ◽  
Author(s):  
Simon Richard Proud
Keyword(s):  
False Positives ◽  
Air Traffic ◽  
The Other ◽  
New Method ◽  
Flight Crew ◽  
International Airport ◽  
Unusual Position ◽  
Position Data ◽  
One Year

The decision of a flight crew to undertake a go-around, aborting a landing attempt, is primarily to ensure the safe conduct of a flight. Although go-arounds are rare, they do cause air traffic disruption, especially in busy airspace, due to the need to accommodate an aircraft in an unusual position, and a go-around can also result in knock-on delays due to the time taken for the aircraft to re-position, fit into the landing sequence and execute a successful landing. Therefore, it is important to understand and alleviate the factors that can result in a go-around. In this paper, I present a new method for automatically detecting go-around events in aircraft position data, such as that sent via the ADS-B system, and apply the method to one year of approach data for Chhatrapati Shivaji Maharaj International Airport (VABB) in Mumbai, India. I show that the method is significantly more accurate than other methods, detecting go-arounds with very few false positives or negatives. Finally, I use the new method to reveal that while there is no one cause for go-arounds at this airport, the majority can be attributed to weather and/or an unstable approach. I also show that one runway (14/32) has a significantly higher proportion of go-arounds than the other (09/27).

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