ORCID Profile
0000-0003-2113-4553
Current Organisations
University of Manchester
,
Universiti Putra Malaysia
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Publisher: The Optical Society
Date: 30-01-2015
DOI: 10.1364/OE.23.002837
Publisher: IEEE
Date: 09-2014
Publisher: IEEE
Date: 09-2014
Publisher: Elsevier BV
Date: 09-2015
Publisher: IEEE
Date: 09-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: IEEE
Date: 04-2015
Publisher: Elsevier BV
Date: 05-2019
Publisher: MDPI AG
Date: 14-02-2023
DOI: 10.3390/BIOS13020270
Abstract: Biosensors are central to diagnostic and medicinal applications, especially in terms of monitoring, managing illness, and public health. Microfiber-based biosensors are known to be capable of measuring both the presence and behavior of biological molecules in a highly sensitive manner. In addition, the flexibility of microfiber in supporting a variety of sensing layer designs and the integration of nanomaterials with biorecognition molecules brings immense opportunity for specificity enhancement. This review paper aims to discuss and explore different microfiber configurations by highlighting their fundamental concepts, fabrication processes, and performance as biosensors.
Publisher: Springer Science and Business Media LLC
Date: 17-07-2019
DOI: 10.1038/S41598-019-46649-Z
Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2021
Publisher: OSA
Date: 2018
Publisher: Penerbit UTM Press
Date: 21-02-2016
DOI: 10.11113/JT.V78.7526
Abstract: The presence of plumbous (Pb2+) in Irrigation water is harmful for the environment as well as human health. Herein, a simple yet effective sensor for Pb2+ detection is presented utilizing a surface plasmon resonance technique. The proposed sensor consists of a combination of 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS) were attached to a gold layer offers a new option for heavy metal detection. The EDC/NHS works as a sensing layer that able to detect Pb2+ down to 15 ppm that matches with the United States Environment Protection Agency.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2016
Publisher: Wiley
Date: 24-04-2018
Abstract: This paper presents the development of tapered optical fiber sensor to detect a specific Leptospira bacteria DNA. The bacteria causes Leptospirosis , a deadly disease but with common early flu‐like symptoms. Optical single mode fiber (SMF) of 125 μm diameter is tapered to produce 12 μm waist diameter and 15 cm length. The novel DNA‐based optical fiber sensor is functionalized by incubating the tapered region with sodium hydroxide (NaOH), (3‐Aminopropyl) triethoxysilane and glutaraldehyde. Probe DNA is immobilized onto the tapered region and subsequently hybridized by its complementary DNA (cDNA). The transmission spectra of the DNA‐based optical fiber sensor are measured in the 1500 to 1600 nm wavelength range. It is discovered that the shift of the wavelength in the SMF sensor is linearly proportional with the increase in the cDNA concentrations from 0.1 to 1.0 nM. The sensitivity of the sensor toward DNA is measured to be 1.2862 nm/nM and able to detect as low as 0.1 fM. The sensor indicates high specificity when only minimal shift is detected for non‐cDNA testing. The developed sensor is able to distinguish between actual DNA of Leptospira serovars (Canicola and Copenhageni) against Clostridium difficile (control s le) at very low (femtomolar) target concentrations.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2018
Publisher: Springer Science and Business Media LLC
Date: 21-07-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Springer Science and Business Media LLC
Date: 17-09-2019
DOI: 10.1038/S41598-019-49891-7
Abstract: The exponential escalation of dengue cases has indeed become a global health crisis. This work elaborates on the development of a biofunctionalized tapered optical fiber (TOF) based sensor with the integration of polyamidoamine (PAMAM) dendrimer for the detection of dengue E protein. The dimension of the TOF generated an evanescent field that was sensitive to any changes in the external medium while the integration of PAMAM promoted more adhesion of bio-recognition molecules anti-DENV II E protein antibodies that were complementary to the targeted protein. This in return created more active sites for the absorption of DENV II E proteins onto the tapered region. The resolution and detection limit of the sensor are 19.53 nm/nM and 1 pM, respectively with K d = 1.02 × 10 −10 M.
Publisher: Elsevier BV
Date: 03-2018
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Muhammad Hafiz Abu Bakar.