Narrow Results

Yak genome provides new insights into high altitude adaptation.

Gentris and Shanghai Institutes of Preventative Medicine expand collaboration.

Chinese researchers identify rice gene enhancing quality, productivity.

Quintiles opens new Center of Excellence in Dalian to support innovative drug development.

BGI demonstrated genomic data transfer at nearly 10 gigabits per second between US and China.

Quintiles deepens investment in China - New Quintiles China Headquarters and local lab testing solution announced.

Beike earns AABB Accreditation for cord blood and cord tissue banking.

Epigenomic differences between newborns and centenarians provide insight to the understanding of aging.

INDIA – Bioven starts BV-NSCLC-001 Phase III trial in NSCLC.

INDIA – Initiative in Chemical Biology and Therapeutics.

PHILLIPPINES – Asia–Pacific Analysis: The slow road to green energy.

SINGAPORE – Takeda progressing well in Asia with New Drug Applications.

SINGAPORE – NTU and University of Warwick boost brainpower in global neuroscience research.

THAILAND – Thai PhD. student awarded Monsanto's Beachell–Borlaug International Scholarship for rice improvement research.

EUROPE – Open access will change the world, if scientists want it to.

UNITED STATES & CANADA – Verisante places Aura Beta Units for safety, verification testing in B.C., Alberta and Ontario clinics.

UNITED STATES & CANADA – Life Technologies sets new worldwide standard for criminal forensic testing with introduction of GlobalFilerTM Express Kit.

UNITED STATES & CANADA – How immune cells can nudge nerves to regrow.

UNITED STATES & CANADA – Improved Genomic Target Selection Using IDT Oligos.

UNITED STATES & CANADA – US team uncover non-invasive method for diagnosing epilepsy.

Scientists decode the genomic sequence of 700,000-year-old horse.

Researchers reveal subepicardial endothelial cells working as major source for coronary arteries in embryonic ventricle wall.

Chinese 'container hospitals' ready to deploy in Africa.

Asian Cancer Research Group and BGI report new evidence for the genetic bases of liver cancer.

Taiwan technology lifts biomedical collaboration.

SIIC to provide funding to biotech projects.

Using Bioinformatics to Understand the Antibody Response.

Genomic Translational Research: From Bench to Bedside.

Understanding DNA-Protein Interactions for Applications in Genome Engineering.

Overview of Bioinformatics Research in Japan.

Perdana University Centre for Bioinformatics: Contributing to the Growth of Bioinformatics in Malaysia.

Bioinformatics for Vaccine Target Discovery.

The Bioinformatics Institute, A*STAR – Innovation in Bits and Bytes.

The Increasing Need for Bioinformatics in Life Science and Biotechnology Research.

SINGAPORE – Asia Pacific Medical Technology Association (APACMed) Announces Partnership with Duke-NUS Medical School’s Centre of Regulatory Excellence (CoRE), Pledging Joint Commitment to Promote Regulatory Convergence and Capacity Building Across the Region.

SINGAPORE – Guardian Partners with MyDoc to Address Singapore’s Population Health Needs through Integrating Technology and Self-Care.

SINGAPORE & UNITED STATES – CellMax Life’s Precision, Non-Invasive Cancer Testing Now Available throughout Southeast Asia through Asia Genomics.

UNITED STATES – 3-D Printed Models Could Improve Patient Outcomes in Heart Valve Replacements.

UNITED STATES – Promising Target to Protect Bone in Patients with Diabetes.

UNITED STATES – New Antibody Appears to Re-Activate Immune System in Cancer Therapy.

UNITED STATES – Combo Immunotherapy May Herald New Standard of Care for Kidney Cancer.

JAPAN – Chugai’s Bispecific Antibody “Emicizumab” Global Phase III Data in Patients with Haemophilia A with Inhibitors Published in The New England Journal of Medicine Online.

RUSSIA & INDIA – BIOCAD’s Rituximab Biosimilar to Receive Market Authorization Soon in India.

The following topics are under this section:

• Providing New Insights to Fighting COVID-19 with AI-Powered Remote Monitoring Platform
• Agreement Signed for Production of Anti-VISTA Antibody for Cancer Clinical Trial
• Exploring the Cancer Genomic Landscape of the Japanese Population
• First Center of Excellence in Singapore to Advance Imaging Mass Cytometry
• RMAT Designation Granted by FDA using CAR-T Cell Therapy for CD-30 Positive Classical Hodgkin Lymphoma
• Expanding Investment for COVID-19 Vaccine Development
• Singapore-based Biotechnology Company Launches Integrated Agri-Food Pilot Facility

There is little consensus about which objective markers should be used to assess major psychiatric disorders, and predict/evaluate treatment response for these disorders. Clinical practice relies instead on subjective signs and symptoms, such that there is a "translational gap" between research findings and clinical practice. This gap arises from: a) a lack of integrative theoretical models which provide a basis for understanding links between gene-brain-behavior mechanisms and clinical entities; b) the reliance on studying one measure at a time so that linkages between markers are their specificity are not established; and c) the lack of a definitive understanding of what constitutes normative function. Here, we draw on a standardized methodology for acquiring multiple sources of genomic, brain and behavioral data in the same subjects, to propose candidate markers of selected psychiatric disorders: depression, post-traumatic stress disorder, schizophrenia, attention-deficit/hyperactivity disorder and dementia disorders. This methodology has been used to establish a standardized international database which provides a comprehensive framework and the basis for testing hypotheses derived from an integrative theoretical model of the brain. Using this normative base, we present preliminary findings for a number of disorders in relation to the proposed markers. Establishing these objective markers will be the first step towards determining their sensitivity, specificity and treatment prediction in individual patients.

Random forest is an ensemble classification algorithm. It performs well when most predictive variables are noisy and can be used when the number of variables is much larger than the number of observations. The use of bootstrap samples and restricted subsets of attributes makes it more powerful than simple ensembles of trees. The main advantage of a random forest classifier is its explanatory power: it measures variable importance or impact of each factor on a predicted class label. These characteristics make the algorithm ideal for microarray data. It was shown to build models with high accuracy when tested on high-dimensional microarray datasets. Current implementations of random forest in the machine learning and statistics community, however, limit its usability for mining over large datasets, as they require that the entire dataset remains permanently in memory. We propose a new framework, an optimized implementation of a random forest classifier, which addresses specific properties of microarray data, takes computational complexity of a decision tree algorithm into consideration, and shows excellent computing performance while preserving predictive accuracy. The implementation is based on reducing overlapping computations and eliminating dependency on the size of main memory. The implementation's excellent computational performance makes the algorithm useful for interactive data analyses and data mining.