Track topics on Twitter Track topics that are important to you
Cancer subtyping is of great importance for the prediction, diagnosis, and precise treatment of cancer patients. Many clustering methods have been proposed for cancer subtyping. In 2014, a clustering algorithm named Clustering by Fast Search and Find of Density Peaks (CFDP) was proposed and published in Science, which has been applied to cancer subtyping and achieved attractive results. However, CFDP requires to set two key parameters (cluster centers and cutoff distance) manually, while their optimal values are difficult to be determined. To overcome this limitation, an automatic clustering method named PSO-CFDP is proposed in this paper, in which cluster centers and cutoff distance are automatically determined by running an improved particle swarm optimization (PSO) algorithm multiple times. Experiments using PSO-CFDP, as well as LR-CFDP, STClu, CH-CCFDAC, and CFDP, were performed on four benchmark data-sets and two real cancer gene expression datasets. The results show that PSO-CFDP can determine cluster centers and cutoff distance automatically within controllable time/cost and, therefore, improve the accuracy of cancer subtyping.
This article was published in the following journal.
Name: Human heredity
Motivated by the concepts of quantum mechanics and particle swarm optimization (PSO), quantum-behaved particle swarm optimization (QPSO) was developed to achieve better global search ability. This pap...
The planning of municipal wastewater treatment networks has been recognized as a valuable means for achieving the optimal use of resources and improving the cost-efficient operation of plants. In this...
There exist many multiobjective optimization problems (MOPs) containing a large number of decision variables in real-world applications, which are known as large-scale MOPs. Due to the ineffectiveness...
A subwavelength metal grating for generating azimuthally polarized beams was designed. The grating material was determined by calculating the total thermal conductivity coefficient. A modified particl...
In this paper, a collaborative neurodynamic optimization approach is proposed for global and combinatorial optimization. First, a combinatorial optimization problem is reformulated as a global optimiz...
We are testing the following two hypotheses: 1) Peaks in hourly exposures to airborne particulate matter (PM) of outdoor origin will be more closely associated with acute asthmatic respons...
The objective of the Continued Access study is to gather confirmatory evidence on the safety of the SonRtip lead and performance of the automatic atrioventricular (AV) delay and interventr...
The design of the study will be randomized, double blind trial, which will examine the effects of Rosiglitazone on the fasting triglycerides (TG), high-density lipoprotein (HDL), HDL parti...
Assessing the volume of the liver before surgery, predicting the volume of liver remaining after surgery, detecting primary or secondary lesions in the liver parenchyma are common applicat...
Primary Objective: To demonstrate the superiority of alirocumab in comparison with usual care in the reduction of non-high-density lipoprotein cholesterol (non-HDL-C) in patients with typ...
Separation of particles according to density by employing a gradient of varying densities. At equilibrium each particle settles in the gradient at a point equal to its density. (McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed)
Low-density subclass of the high-density lipoproteins, with particle sizes between 8 to 13 nm.
A technique used to separate particles according to their densities in a continuous density gradient. The sample is usually mixed with a solution of known gradient materials and subjected to centrifugation. Each particle sediments to the position at which the gradient density is equal to its own. The range of the density gradient is usually greater than that of the sample particles. It is used in purifying biological materials such as proteins, nucleic acids, organelles, and cell types.
Intermediate-density subclass of the high-density lipoproteins, with particle sizes between 7 to 8 nm. As the larger lighter HDL2 lipoprotein, HDL3 lipoprotein is lipid-rich.
A highly dense subclass of the high-density lipoproteins, with particle sizes below 7 nm. They are also known as nascent HDL, composed of a few APOLIPOPROTEIN A-I molecules which are complexed with PHOSPHOLIPIDS. The lipid-poor pre-beta-HDL particles serve as progenitors of HDL3 and then HDL2 after absorption of free cholesterol from cell membranes, cholesterol esterification, and acquisition of apolipoproteins A-II, Cs, and E. Pre-beta-HDL initiate the reverse cholesterol transport process from cells to liver.
Cancer is not just one disease but many diseases. There are more than 100 different types of cancer. Most cancers are named for the organ or type of cell in which they start - for example, cancer that begins in the colon is called colon cancer; cancer th...
Bladder Cancer Brain Cancer Breast Cancer Cancer Cervical Cancer Colorectal Head & Neck Cancers Hodgkin Lymphoma Leukemia Lung Cancer Melanoma Myeloma Ovarian Cancer Pancreatic Cancer ...
The process of gene expression is used by eukaryotes, prokaryotes, and viruses to generate the macromolecular machinery for life. Steps in the gene expression process may be modulated, including the transcription, RNA splicing, translation, and post-tran...