Search results for " Bioinformatics"
showing 4 items of 74 documents
A one class classifier for Signal identification: a biological case study
2008
The paper describes an application of a one-class KNN to identify different signal patterns embedded in a noise structured background. The problem become harder whenever only one pattern is well represented in the signal, in such cases one class classifier techniques are more indicated. The classification phase is applied after a preprocessing phase based on a Multi Layer Model (MLM) that provides a preliminary signal segmentation in an interval feature space. The one-class KNN has been tested on synthetic data that simulate microarray data for the identification of nucleosomes and linker regions across DNA. Results have shown a good recognition rate on synthetic data for nucleosome and lin…
PD-1/PD-L1 immune-checkpoint blockade induces immune effector cell modulation in metastatic non-small cell lung cancer patients: A single-cell flow c…
2022
Peripheral immune-checkpoint blockade with mAbs to programmed cell death receptor-1 (PD-1) (either nivolumab or pembrolizumab) or PD-Ligand-1 (PD-L1) (atezolizumab, durvalumab, or avelumab) alone or in combination with doublet chemotherapy represents an expanding treatment strategy for metastatic non-small cell lung cancer (mNSCLC) patients. This strategy lays on the capability of these mAbs to rescue tumor-specific cytotoxic T lymphocytes (CTLs) inactivated throughout PD-1 binding to PD-L1/2 in the tumor sites. This inhibitory interactive pathway is a physiological mechanism of prevention against dangerous overreactions and autoimmunity in case of prolonged and/or repeated CTL response to …
SNPs detection by eBWT positional clustering
2019
Sequencing technologies keep on turning cheaper and faster, thus putting a growing pressure for data structures designed to efficiently store raw data, and possibly perform analysis therein. In this view, there is a growing interest in alignment-free and reference-free variants calling methods that only make use of (suitably indexed) raw reads data. We develop the positional clustering theory that (i) describes how the extended Burrows–Wheeler Transform (eBWT) of a collection of reads tends to cluster together bases that cover the same genome position (ii) predicts the size of such clusters, and (iii) exhibits an elegant and precise LCP array based procedure to locate such clusters in the e…