[HTML][HTML] ccImpute: an accurate and scalable consensus clustering based algorithm to impute dropout events in the single-cell RNA-seq data
Background In recent years, the introduction of single-cell RNA sequencing (scRNA-seq)
has enabled the analysis of a cell's transcriptome at an unprecedented granularity and …
has enabled the analysis of a cell's transcriptome at an unprecedented granularity and …
Investigating the performance of hardware transactions on a multi-socket machine
The introduction of hardware transactional memory (HTM) into commercial processors
opens a door for designing and implementing scalable synchronization mechanisms. One …
opens a door for designing and implementing scalable synchronization mechanisms. One …
Engineering ultimate self-protection in autonomic agents for space exploration missions
R Sterritt, M Hinchey - … and Workshops on the Engineering of …, 2005 - ieeexplore.ieee.org
NASA's Exploration Initiative (EI) will push space exploration missions to the limit. Future
missions will be required to be self-managing as well as self-directed, in order to meet the …
missions will be required to be self-managing as well as self-directed, in order to meet the …
[HTML][HTML] Using data to build a better EM: EM* for big data
H Kurban, M Jenne, MM Dalkilic - … Journal of Data Science and Analytics, 2017 - Springer
Existing data mining techniques, more particularly iterative learning algorithms, become
overwhelmed with big data. While parallelism is an obvious and, usually, necessary …
overwhelmed with big data. While parallelism is an obvious and, usually, necessary …
Em*: An em algorithm for big data
H Kurban, M Jenne, MM Dalkilic - 2016 IEEE International …, 2016 - ieeexplore.ieee.org
Existing data mining techniques, more particularly iterative learning algorithms, become
overwhelmed with big data. While parallelism is an obvious and, usually, necessary …
overwhelmed with big data. While parallelism is an obvious and, usually, necessary …
Red-rf: Reduced random forest for big data using priority voting & dynamic data reduction
Random Forests have been used as effective ensemble models for classification. We
present in this paper a new type of Random Forests (RFs) called Red (uced) RF that adopts …
present in this paper a new type of Random Forests (RFs) called Red (uced) RF that adopts …
Predicting Atom Types of Anatase TiO2 Nanoparticles with Machine Learning
Machine learning (ML) has recently made a major contribution to the fields of Material
Science (MS). In this study, ML algorithms are used to learn atoms types over structural …
Science (MS). In this study, ML algorithms are used to learn atoms types over structural …
Metin Madenciliği ile Tıbbi Tedavi Alanlarının Yakınlıklarının Ölçülmesi
H Kurban - Avrupa Bilim ve Teknoloji Dergisi, 2021 - dergipark.org.tr
Bazı hastalık belirtilerinin birçok tıbbi tedavi alanıyla ilgili olması, hastaların tedavi için
randevu alırken zorlanmalarına sebep olmaktadır. Örneğin; karın ağrısı rahatsızlığı bulunan …
randevu alırken zorlanmalarına sebep olmaktadır. Örneğin; karın ağrısı rahatsızlığı bulunan …
[PDF][PDF] ccImpute: anaccurate andscalable consensus clustering based algorithm toimpute dropout events inthesingle-cell RNA-seq data
Background: In recent years, the introduction of single-cell RNA sequencing (scRNA-seq)
has enabled the analysis of a cell's transcriptome at an unprecedented granularity and …
has enabled the analysis of a cell's transcriptome at an unprecedented granularity and …
Improving expectation maximization algorithm over stellar data
H Kurban, C Kockan, M Jenne… - 2017 IEEE International …, 2017 - ieeexplore.ieee.org
Stellar data, only a few years ago, measured in the. 1M of objects. Now, sets are routinely
1M. With the launch of ESA's Gaia in 2013, we expect 1000M stellar objects measured more …
1M. With the launch of ESA's Gaia in 2013, we expect 1000M stellar objects measured more …