Not exact matches
Based on the ribosome
profiling data, the researchers looked for
genes that were being expressed differently in the trained mice, identifying 104
genes in total.
Based on how the
genes fit within the original, mapped
profile, they can predict with a high accuracy if a particular patient will develop metastatic tumors.
The resulting «map» of
gene - drug interactions allowed the researchers to accurately predict the responses of multiple human cancer cell lines to different chemotherapy agents
based on the cell lines» genetic
profiles and also revealed new genetic factors that appear to determine the response of breast and ovarian tumor cells to common classes of chemotherapy treatment.
The findings, which came out online June 26, 2015, in the journal Neuropsychopharmacology, are hopeful news amid a new national push toward «precision medicine,» in which doctors will tailor drug regimens and other treatments
based on patients» individual
gene profiles or other factors.
Previously, genetic counselors tested a small number of
genes sequentially
based on family
profile and tumor analysis until the culprit was identified.
Bengt Nordéns contribution to form a strong research school in Gothenburg has been successful: as many as 12 out of his about 50 former PhD students and postdocs have become professors, abroad or at other Swedish universities, and three have returned to contribute a forceful environment with their own
profiles within the Department: Prof Bo Albinsson (femtosecond spectroscopy and fundamentals of electron transfer), Prof Per Lincoln (new transition - metal -
based DNA ligands and statistical mechanics for
gene targeting), Prof Björn Åkerman (fundamentals and applications of DNA physical chemistry).
Exon -
Based Transcriptome
Profiling Reveals
Genes That Have Prognostic Impact on the Survival of Young High Risk Diffuse Large B - Cell / Follicular Grade 3 Lymphoma Patients Treated with Dose - Dense Chemoimmuno - therapy and CNS Prophylaxis.
Use of exon -
based transcriptome
profiling to identify novel signaling pathways and survival - associated
genes in diffuse large B - cell lymphoma.
The 12th release of the Human Protein Atlas (HPA) covers 16,621
genes (approximately 83 % of the human protein - coding
genes) and includes protein expression
profiles based on 21,984 antibodies.
We offer a wide range of services, including capillary sequencing and genotyping, Illumina microarray -
based gene expression
profiling and genotyping, and next - generation sequencing (NGS).
This is an advantage of RNA - seq and microarray -
based expression
profiling, which can't always distinguish between multiple promoters of the same
gene.
This version covers 15,156
genes (approximately 75 % of human protein - coding
genes) and includes protein expression
profiles based on 18,707 antibodies.
In recent years DNA - and RNA -
based surveys of tumor genome and expression
profiling have produced a plethora of leads on
genes with clinical significance.
We use three sources of information to update the homology -
based immune catalog in Nasonia: a previously published catalog of antimicrobial peptides [35], homology to characterized Dipteran immune proteins
based on reciprocal best blastp hits to D. melanogaster, and
profile hidden Markov models (HMMs) of known immune - related
gene families derived from ImmunoDB [11](see methods for details).
In addition, University of Michigan has developed one of the nation's largest and most sophisticated
gene sequencing programs, allowing for customization of treatment plans
based on each child's own genetic cancer
profile.
The set of possible analyses include: 1) comparison of cell populations for the identification of differentially expressed
genes; 2) dimensionality reduction for the identification of relevant coordinates; and 3) clustering of subpopulations on the
base of
gene expression
profiles.
These include: a) Global Clusters that consist of a small, tight subset of
genes that are co-expressed under the entire spectrum of experimental conditions; b) Time Series of
gene expression profiles during successive days of standard ES cell differentiation; c) Specific Gene Classes based on hierarchical clustering of transcriptional factors and ESTs; d) Expression Waves of genes with characteristic expression profiles during ES cell differentiation, juxtaposed to waves of genes that behave in the exact opposite way; e) Pathway Animations that illustrate dynamic changes in the components of individual KEGG signaling and metabolic pathways viewed in time - related manner; and, f) Search Engines to display the expression pattern of any transcript, or groups of transcripts, during the course of ES cell differentiation, or to query the association of candidate genes with various FunGenES database clust
gene expression
profiles during successive days of standard ES cell differentiation; c) Specific
Gene Classes based on hierarchical clustering of transcriptional factors and ESTs; d) Expression Waves of genes with characteristic expression profiles during ES cell differentiation, juxtaposed to waves of genes that behave in the exact opposite way; e) Pathway Animations that illustrate dynamic changes in the components of individual KEGG signaling and metabolic pathways viewed in time - related manner; and, f) Search Engines to display the expression pattern of any transcript, or groups of transcripts, during the course of ES cell differentiation, or to query the association of candidate genes with various FunGenES database clust
Gene Classes
based on hierarchical clustering of transcriptional factors and ESTs; d) Expression Waves of
genes with characteristic expression
profiles during ES cell differentiation, juxtaposed to waves of
genes that behave in the exact opposite way; e) Pathway Animations that illustrate dynamic changes in the components of individual KEGG signaling and metabolic pathways viewed in time - related manner; and, f) Search Engines to display the expression pattern of any transcript, or groups of transcripts, during the course of ES cell differentiation, or to query the association of candidate
genes with various FunGenES database clusters.
Although the database described here was
based on the
gene expression
profiling results of the FunGenES consortium, it can be easily adapted to incorporate available or future genomics data obtained in ES cells.
Rohit presented his work on using machine learning applications for predicting prognosis in primary melanoma
based on
gene expression
profiles derived from primary melanoma tumours.
The power of the statistical algorithm was illustrated by the researchers» ability to further subdivide the patients» genetic
profiles on the
basis of individual
genes.
On a safari through the genome —
genes offer new insights into the distribution of giraffes (17/11/2014) A team from the LOEWE Biodiversity and Climate Research Center (BiK - F), in conjunction with the Giraffe Conservation Foundation, has conducted a detailed analysis of these animals» spatial distribution
based on their genetic
profile....
Although many common
genes were expressed in the three tissues, cluster analysis
based on transcript levels revealed distinct
gene expression
profiles of the d - 18 EET (Fig. 2C and SI Appendix, Fig.
Based on the
gene expression
profile, we demonstrated the up - regulation of hormone sensitive lipase and enhancement of the lipolytic activity by the treatment of adipocytes with C3G or Cy.