L1 Least Square for Cancer Diagnosis using Gene Expression Data

Hang, Xiyi; Wu, Fang-Xiang

doi:10.4172/jcsb.1000028

Cited by 7 publications

(5 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The root-finding framework for the particular case where κ(x) = x 1 was first described in [5], and implemented in the SPGL1 [4] software package. The success of the SPGL1 package in practice-see, e.g., [19,36,37,39,46,62,64]-motives us to provide a unified algorithm that applies to a wider class of problems, including sign-restricted basis pursuit denoise, sum-of-norms, and matrix completion problems.…”

Section: Related Workmentioning

confidence: 99%

Sparse Optimization with Least-Squares Constraints

Berg¹,

Friedlander²

2011

SIAM J. Optim.

201

120

View full text Add to dashboard Cite

The use of convex optimization for the recovery of sparse signals from incomplete or compressed data is now common practice. Motivated by the success of basis pursuit in recovering sparse vectors, new formulations have been proposed that take advantage of different types of sparsity. In this paper we propose an efficient algorithm for solving a general class of sparsifying formulations. For several common types of sparsity we provide applications, along with details on how to apply the algorithm, and experimental results.

show abstract

Section: Related Workmentioning

confidence: 99%

Sparse Optimization with Least-Squares Constraints

Berg¹,

Friedlander²

2011

SIAM J. Optim.

201

120

View full text Add to dashboard Cite

show abstract

“…Linear regression as a constrained l1-norm minimization problem greatly alleviate its sensitivity to outliers, and hence the name l1 least square. The numerical experiment shows that l1 least square can match the best performance achieved by support vector machines (SVMs) with careful model selection [36]. Humans have been carrying unwanted viral gene segments since many years and reports suggests that approximately 3-8% of the human genome has been comprised of viral DNA.…”

Section: Genomicsmentioning

confidence: 99%

Emerging Trends in Various Fields with Systems Biology Approach

N¹,

ikolla²,

Shaik³

et al. 2011

J Comput Sci Syst Biol

View full text Add to dashboard Cite

JCSB, an open access journal Systems Biology is also associated with disciplines likePhenomics -is a study concerned with the measurement of phenomes, the biochemical and physical traits of organisms with respect to their change in response to environmental influences and genetic mutation. Genomics -the study of the organisms genome is called genomics. This field includes derives the entire DNA sequence of organisms and finescale genetic mapping efforts. Epigenetics -study of heritable changes in cellular phenotype or gene expression caused by mechanisms other than changes happen in DNA sequenceTranscriptomics -the set of all RNA molecules is called transcriptome, which includes mRNA, rRNA, tRNA, and other noncoding RNA. This study of transcriptome is called Transcriptomics.Interactomics -it is a combined subject of bioinformatics and biology which deals with both the interactions and the consequences of protein-protein interactions, and other cellular molecules [3].Interferomics -the study of post-transcriptomic vanges and pretranslatomic changes.Translatomics or Proteomics -is the study of proteins, in particular of their structures and functions [4,5]. Proteins are essential for living organisms, as they are the main components of the metabolic pathways of cells.Metabolomics -study of the unique chemical fingerprints which leaves behind specific cellular processes, the study of these profiles of small-molecule metabolite is called Metabolomics [6].Glycomics -the study of all glycans of a given cell type or organism. This comes under glycobiology.Lipidomics -the large-scale study of networks and pathways of cellular lipids in biological systems [7,8].NeuroElectroDynamics -the study of the dynamics and interaction of electrical charges in the brain [9].Fluxomics -a mathematical method for analysing metabolism is known as fluxomics. Knowledge of concentrations of metabolites or the details of enzyme kinetics of the system is not required for this mathematical method.Biomics -is the biological knowledge of Biomes, and the processing of that information, like ecological communities of plants, animals, and micro organisms comes under biomics.Biological function can be understood if we are able to integrate all relevant information at multiple levels of organization to recreate dynamic interactions. Mathematical and computational models together explain the underlying complex interacting non-linear processes in biological function which cannot be recreated by experimental observation [10].System Biology studies paved a huge role in various fields. The recent developments in some the fields are noted below.

show abstract

“…The l 1 least square classifier may become a promising automatic cancer diagnosis tool by consistently distinguishing gene profile classes. Those genes with great absolute regression coefficients may serve as biological marker candidates for further investigation [37,38]. Damage analysis in metabolic pathways is one of the most highlighted fields in systems biology area.…”

Section: Lipid Biomarkers In Chronic Diseasementioning

confidence: 99%

Lipidomics: A Promising area in “OMICS” Research

Tripathy¹

2012

JCSB

View full text Add to dashboard Cite

Lipidomics is defined as the analysis of lipids on the systems-level scale together with their interacting factors. In this review, we will discuss the technical developments in the field of lipidomics and overview the current state of the lipid bioinformatics field as well as suggest few potential new areas of research. The role of bioinformatics in the development of lipidomics will also be discussed.

show abstract

L1 Least Square for Cancer Diagnosis using Gene Expression Data

Cited by 7 publications

References 21 publications

Sparse Optimization with Least-Squares Constraints

Sparse Optimization with Least-Squares Constraints

Emerging Trends in Various Fields with Systems Biology Approach

Lipidomics: A Promising area in “OMICS” Research

Contact Info

Product

Resources

About