Results 261 to 270 of about 187,728 (325)

Feeding dysfunction in a neonate with interstitial deletion of chromosome 2q24.3-q32.1: a case report. [PDF]

open access: yesBMC Pediatr
Alvarado-Ramos N   +6 more
europepmc   +1 more source

Mast Cells in Acute COVID‐19 Patients

open access: yes
Allergy, EarlyView.
Ilan Zaffran   +8 more
wiley   +1 more source

Cost-effective and flexible preimplantation genetic testing (PGT) by nanopore adaptive sampling. [PDF]

open access: yesJ Nanobiotechnology
Zhang Z   +15 more
europepmc   +1 more source

Monitoring of haematopoietic stem cell mobilization by targeted DNA methylation analysis for the British Journal of Haematology

open access: yes
British Journal of Haematology, EarlyView.
Wouter H. G. Hubens   +3 more
wiley   +1 more source

Pattern Recognition Techniques in Microarray Data Analysis

open access: closedAnnals of the New York Academy of Sciences, 2002
Abstract:Recent development of technologies (e.g., microarray technology) that are capable of producing massive amounts of genetic data has highlighted the need for new pattern recognition techniques that can mine and discoverbiologically meaningfulknowledge in large data sets.
Faramarz Valafar
exaly   +4 more sources

A colon cancer microarray analysis technique

open access: closed2017 E-Health and Bioengineering Conference (EHB), 2017
Colon cancer is a very spread malady at international level, symptoms occurring due to a number of vary conditions that may be totally ignored in early stages. Moreover, even treated surgical or with chemotherapy, lots of patients occur recurrence at a specific period of time, so more validated findings in the microarray analysis field, should improve ...
Irina-Oana Lixandru-Petre   +1 more
openalex   +2 more sources

Analysis techniques for microarray time-series data

Proceedings of the fifth annual international conference on Computational biology, 2001
We address possible limitations of publicly available data sets of yeast gene expression. We study the predictability of known regulators via time-series analysis, and show that less than 20% of known regulatory pairs exhibit strong correlations in the Cho/Spellman data sets.
Vladimir Filkov, Steven Skiena, Jizu Zhi
openaire   +2 more sources

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