12: Module 10: Biotechnology - Biology

12: Module 10: Biotechnology - Biology

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12: Module 10: Biotechnology

12: Module 10: Biotechnology - Biology

Biotechnology is a precious gift to the 21st century as it has drastically changed the future of our planet. Biotech has proven its importance in almost every field and it holds the ability to change the world. The Program aims to impart knowledge and understanding of the different aspects of life sciences and biotechnology. These programs are designed to prepare students to meet the needs of growing industrial base by providing knowledge in several different areas of biological science that make up the basis of biotechnology. By integrating the knowledge and information presented in courses prepared by faculty from the different departments of Biotechnology will prepare students to meet and exceed the expectations of growing industrial base. The global biotechnology industry comprises a diverse range of companies engaged in the development of pharmaceuticals, best resistant crops and biofuels. Revenue for the industry has grown over the past 5 years and global investment in biotechnology has increased consistently, with much of the added R&D spending funnelled into medical applications aim at providing care for the aging global population. The industry expected to continue prospering over the next 5 years, with the Asia Pacific region making significant investment to gain a foothold in the market. By doing this course well, participant will develop basic knowledge and skills in cell, molecular biology, genetic engineering, plant and animal biotechnology, fermentation technology and many subjects related to biotech.

  • Module 1: Identify major differences in project/dissertation/thesis work.
  • Module 2: Develop the new idea and create the key components for research work.
  • Module 3:Develop scientific skills and gather the critical scientific information to write a report.
  • Module 4: Comparison of different types of paper for publication.
  • Module 5: Criteria for evaluating a journal for paper publication.
  • Module 6: Understand the Basic concept of Impact factor.
  • Module 7: Design effective scientific approach to write a paper for publication.
  • Module 8: Learning of procedures for submitting a research paper to a professional journal for publication.
2. Advance Certificate Program in industrial Microbiology and enzymology (BT-02)
  • Module 1: Introduction to Industrial Microbiology.
  • Module 2: Choosing Microorganism for industrial purpose.
  • Module 3: Microorganism growth in controlled environment.
  • Module 4: Screening and microbial growth strain improvment for overproduction of industrial products.
  • Module 5: Introduction about enzymology and overview of microbial therapeutics enzymes.
  • Module 6:Enzymes with special characteristics in biotechnology.
  • Module 7: Production and purification of microbial enzymes.
  • Module 8: Analytical and industrial application of microbial enzymes.
  • Module 9: Review writing.
  • Module 10: Paper Publication.
3. Advance Certificate Program in CRISPR/CAS-9 TECHNOLOGY FOR GENE EDITING
  • Module 1:Fundamentals of Molecular Biology Concepts and Processes.
  • Module 2: Conventional and Advanced Genetic Engineering and Genome-editing.
  • Module 3: Historical Perspective of CRISPR Discovery and Development of CRISPR/Cas Technology. gRNA, PAM CRISPR locus, CAS9, CPF1 and CAS-FISH.
  • Module 4: Current Application and potential scope of CRISPR/Cas9 Technology.
  • Module 5: Challenges in CRISPR/Cas9 Technology.
  • Module 6: Bioinformatics and Computational based Technical Requirement.
  • Module 7: Screening and Specificity of CRISPR/Cas9 System (CRISPR on-target and off-target analysis).
  • Module 8:CRISPR Technology and Personalized Medicine.
  • Module 9:Application of Next Generation Technology in CRISPR Technology.
  • Module 10: Ethical and regulatory issues related to CRISPR Technology.
  • Module 11: Review writing.
  • Module 12: Paper Publication.
  • Module 1:Fundamentals of molecular biology, DNA structure & gene expression.
  • Module 2:Chromosome structure & function.
  • Module 3:Molecular biology techniques (methods and tools for studying genes).
  • Module 4:Recombinant DNA technology, transgenic plants & animals.
  • Module 5:Novel drugs & new therapies for genetic diseases.
  • Module 6:Gene therapy and its future scope.
  • Module 7:Review Writing.
  • Module 8:Paper Publication.
5. Advance Certificate Program in BIOPHARMACEUTICALS (BT-05)
  • Module 1: Introduction and application of Biopharmaceuticals.
  • Module 2: Guide to analytical testing of Biopharmaceuticals.
  • Module 3: Challenges and opportunities in Biopharmaceutical manufacturing.
  • Module 4: Production and analytical method validation for Biopharmaceuticals.
  • Module 5: Industrial scale fermentation and filter options for Biopharmaceutical production.
  • Module 6: Upstream and Downstream process development for antibody manufacturing.
  • Module 7:Biopharmaceuticals from microorganisms: from production to purification.
  • Module 8: New drug development in Biopharmaceutical companies.
  • Module 9: Progress in Biopharmaceutical development.
  • Module 10:Ethical considerations in the testing of Biopharmaceuticals.
6. Diploma Certificate Program in ANIMAL CELL CULTURE TECHNOLOGY (BT-06)
  • Module 1:General introduction to cells, cell lines and animal cell culture.
  • Module 2: Basic technique in animal cell culture .
  • Module 3:Characterization of cells.
  • Module 4:Contamination in cell culture .
  • Module 5:Three dimensional cell culture .
  • Module 6:Large-scale animal cell cultures: Design and operational considerations.
  • Module 7:Recent advances of mammalian cells for biopharmaceutical production.
  • Module 8:Animal cell cultures: Risk assessment and biosafety recommendations.
7. Diploma Certificate Program in vaccine development & Biomanufacturing (BT-07)
  • Module 1: Introduction and importance of vaccines and vaccination.
  • Module 2: Key steps in vaccine development.
  • Module 3: Mechanism of action of vaccine.
  • Module 4:New technologies for vaccine development.
  • Module 5:Monoclonal antibody based therapies for microbial diseases.
  • Module 6:Plant based vaccines for animals and humans.
  • Module 7:Guidelines for clinical and non-clinical evaluation of vaccines.
  • Module 8: The current challenges for vaccine development.
  • Module 9:Estimating the full public health value of vaccination.
  • Module 10:Intellectual Property Rights and vaccines.
  • Module 1:Fundamentals of Microbial Biotechnology.
  • Module 2:Industrial microorganisms.
  • Module 3:Microbial Cell Structure and Function.
  • Module 4:Cultivation of microoganisms.
  • Module 5:Production of biologicaly active substances by bacteria, fungi.
  • Module 6:Interactions with Microorganisms, Plants and Animals .
  • Module 7:Beneficial microbes: Food microbiology (organisms in dairy and meat products, factors effecting growth).
  • Module 8:Fermentation and Probiotics.
9. Diploma Certificate Program in NANOBIOTECHNOLOGY AND NANOMEDICINE (BT-9)
  • Module 1:Introduction of nanoscience and nanotechnology and its application.
  • Module 2: Classification and manufacturing of nanomaterials .
  • Module 3: Overview on gold , silver and metallic nanoparticles and their physicochemical characterization.
  • Module 4:Scope of nanoscience and nanotechnology in agriculture .
  • Module 5: Advances in nanosheet technology towards nanomedical engineering.
  • Module 6:Carbon nanotubes: A new biotechnological tool on the diagnosis and treatment of cancer .
  • Module 7: Nanoscale drug delivery systems.
  • Module 8:Nanomaterials for healthcare biosensing applications.
  • Module 1:Fundamental of microbiology.
  • Module 2:Human microbiome in health and disease.
  • Module 3: Laboratory diagnosis: Microscopy, in vitro culture techniques, molecular and serologic diagnosis.
  • Module 4: Application of Real-time PCR in the microbiology laboratory.
  • Module 5: Smartphone-based clinical diagnostics.
  • Module 6:Introduction to molecular diagnosis.
  • Module 7:Diseases and molecular diagnostics: A step closer to precision Medicine.
  • Module 8: Microbial genetics: Gene expression and genetic engineering.
  • Module 9: Molecular biomarkers for the early detection of Lung Cancer
  • Module 10: Diagnostic molecular microbiology and its applications: Current and future perspectives
11. Diploma Program in Recombinant DNA technology, Genetic Engineering & ITS INDUSTRIAL APPLICATIONS(BT-11)
  • Module 1:Introduction of recombinant DNA technology (RDT), structure and function of DNA.
  • Module 2:Biological tools of recombinant DNA technology.
  • Module 3: Role of recombinant DNA technology for crop improvement.
  • Module 4: Strain improvement in industrial microorganisms by recombinant DNA techniques.
  • Module 5: New drugs and new therapies for genetic diseases.
  • Module 6: Recombinant DNA technology and environmental biotechnology.
  • Module 7: Application of recombinant DNA technology in food and food ingredients.
  • Module 8:Protein engineering and production of antibodies and their derivatives .
  • Module 9: Recombinant drugs development by biopharmaceuticals.
  • Module 10: Application in combating infectious disease.
  • Module 11: Application of recombinant DNA technology to the production of beneficial
  • Module 12: The scope and limits of regulation of recombinant DNA technology.
  • Module 13: Review writing.
  • Module 14: Paper Publication.
  • Module 1: Forensic science: Basic, professional ethics, quality and justice.
  • Module 2: General principles of crime scene investigation and Collection and preservation of evidence.
  • Module 3: Staff skill requirements and equipment recommendations for forensic science laboratories.
  • Module 4: Forensic significance of physical evidences in crime scene investigation.
  • Module 5: Introduction of DNA fingerprinting.
  • Module 6: DNA fingerprinting and DNA forensic.
  • Module 7: Recent advances in forensic DNA analysis.
  • Module 8: DNA fingerprinting as an evidence and role of Indian supreme court.
  • Module 9: Issues and challenges with forensic DNA analysis.
  • Module 10: DNA fingerprinting in forensics: past, present and future.
  • Module 11: Review writing.
  • Module 12: Paper Publication.

Module 1: Introduction of Natural products as lead compounds for drug development.
Module 2: Comparison between the traditional medicine and modern medicine from natural products.
Module 3: Understand the relationship between natural products and synthetic chemistry in the drug discovery process .
Module 4: Role of Phytoconstituents and their different mode of standard extractions .
Module 5: Need of Standardization of herbal medicines.
Module 6: Ethno medicines and their used in antiviral drug discovery.
Module 7: Challenges of tropical medicinal herbs and modern drug discovery.
Module 8: WHO Guidelines on safety monitoring of herbal medicines in pharmacovigilance Systems.
Module 9: Global Scenario of Herbal medicine for market potential.
Module 10: Analysis of parameters: Quality control, screening, toxicity, and regulation of herbal drugs.
Module 11: Review Writing
Module 12: Paper Publication

114. Diploma certificate Program in Stem Cell Therapeutic and Regenerative Medicine (BT-14).
  • Module 1:Basic concepts and clinical application of stem cells.
  • Module 2: Embryonic and non- embryonic stem cells.
  • Module 3:Researches on regenerative medicine: Current state and prospect.
  • Module 4: Stem cell therapy and their role in cancer treatment.
  • Module 5:Application of neural stem cells to neuroregeneration.
  • Module 6:Cell cycle control of stem cell fate.
  • Module 7: Postnatal stem cells for myocardial repair.
  • Module 8: Stem cell therapy for stroke.
  • Module 9: Stem cells used in skeletal muscle regeneration.
  • Module 10: Liver stem cells and regenerative medicine.
  • Module 11: Clinical manufacture for production of stem cells.
  • Module 12: Ethical and social considerations of stem cell research.
  • Module 13: Review writing.
  • Module 14: Paper Publication.
Program Code Indian Candidates (Rs.) International Candidates (Dollar $)
1 Month 3 Months 6 Months
BI-01 Rs. 10000 (200$) Rs. 20000 (400$) NIL
BI-02 Rs. 10000 (200$) Rs. 20000 (400$) NIL
BI-03 Rs. 10000 (200$) Rs. 20000 (400$) NIL
BI-04 Rs. 10000 (200$) Rs. 20000 (400$) NIL
BI-05 Rs. 10000 (200$) Rs. 20000 (400$) NIL
BI-06 Rs. 10000 (200$) Rs. 20000 (400$) NIL
BI-07 Rs. 10000 (200$) Rs. 20000 (400$) NIL
BI-08 Rs. 10000 (200$) Rs. 20000 (400$) NIL
BI-09 Rs. 10000 (200$) Rs. 20000 (400$) NIL
BI-10 Rs. 10000 (200$) Rs. 20000 (400$) Rs. 30000 (400$)
BI-11 Rs. 10000 (200$) Rs. 20000 (400$) Rs. 30000 (400$)
BI-12 Rs. 10000 (200$) Rs. 20000 (400$) Rs. 30000 (400$)
BI-13 Rs. 10000 (200$) Rs. 20000 (400$) Rs. 30000 (400$)
BI-14 Rs. 10000 (200$) Rs. 20000 (400$) Rs. 30000 (400$)

Persons pursuing or passed out of B.Sc. / M.Sc. / B.Tech/ M.Tech/ in Biotechnology, Bioinformatics, Microbiology & other relevant Qualification in the respective areas are eligible.

At the end of the duration of a program, student go through a well-defined evaluation. Grades are given according to their performance in exam and then certificate is awarded.

There are great opportunities for being a scientist in Biotechnology, it includes a high level of research work regarding health, agriculture, animal, plant and so on. You can get job opportunities in crime laboratory where you will get the job of DNA testing and help police to find the criminal. Pharmaceuticals industry is another lucrative sector for the students of Biotechnology. Microbial work in any industry needs students of Biotechnology. Antibiotic, insulin and other important lifesaving medicines production is directly connected with Biotechnology. It can be said that Biotechnology has touched most areas of our life, so the career opportunities in this field is basically unlimited. They are:

  • Project Assistant
  • Project Associate
  • Technical Assistant
  • Clinical laboratory technician
  • Crime scene technician
  • Forensic Chemist
  • Biotechnology Consultant and MANY MORE…

Select Distance Learning Program of your choice

Fill online application form & Pay fees

Confirmation of admission & enrollment number

Dispatch of Course material

Download & submit Assignment

Award of Certificate based on performance in Assignment

Step 1- Click on “Apply Online Form from the website.

Step 2 - Completely fill application form and submit online.

Step 3- Submit application fee using NEFT from anywhere in India.

Name of the Account: Rapture Biotech International Pvt. Ltd.

Account Number: 2612431210

IFSC Code: KKBK0005033

Submit fee using DD/Cheques. Should be Drawn In favour of Rapture Biotech payable at Noida and send it to "Rapture Biotech, D-201, Sector 10 Noida - 201301, Uttar Pradesh" by Speed Post/Registered Post.

(For International Students): Bank to Bank Transfer by Swift Mode.
Bank Name:Kotak Mahindra Bank,Sec-18, Noida
Name of the Account:Rapture Biotech International Pvt Ltd
Account Number:2612431210
IFSC Code:KKBK0005033

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Free Download Allen Biology Module In Gujarati

Download Allen Biology Module In Gujarati. Allen Study Material of Physics, Chemistry & Biology Modules PDF with theory & questions for NEET 2020 Preparation available for free download. Download all Allen Biology Module in Gujarati Allen DLP modules & Allen Handbook in the form of PDF from Technicalgurugi. All Allen download links are of google drive for fast download without any ads. Allen Kota’s study materials are scanned so that they may vary in sizes and shapes or contrast. Allen’s study materials are useful for your Neet 2020 preparation or NEET 2020 preparation. So this Allen study material for Neet is free of cost, and no registration required. You can also download Allen NEET 2020 Minor Test series paper and Aakash Neet test papers by checking Technicalgurugi’s blog .

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Textbook: Exploring Creation with Biology (Apologia, ISBN 978-1-932012-54-5)

Laboratory notebook: Permanently-bound (NOT spiral-bound) lab notebook with at least 100 perforated, carbonless duplicates. I recommend Barbakam brand (ISBN 978-0-9785344-5-5, R.O.C.K. Solid usually has this in stock per my request and it can be ordered here)

Laboratory kit: Microscope slides are recommended to earn the lab credit for this class. A microscope with 40X, 100X, and 400X optical magnification is necessary, similar to this product. Dissection tools and a specimen kit compatible with the textbook listed above are also needed. It doesn't have to be purchased from Apologia sometimes you can find better prices from Home Science Tools, Nature's Workshop Plus, or other homeschool resources. Just be sure it is marked as compatible with the Apologia Biology curriculum. The first dissection is in Module 11, so it is best to wait on ordering the specimens so they don't dry out too much.

MSc Plant Science and Biotechnology

Develop your expertise in molecular plant science and its application.

Unprecedented progress has been made in the study of plant biology with the development of new tools and technologies. This knowledge contributes to the development of sustainable solutions to many major challenges of the 21st century such as food, energy and materials. On this course our world-leading academics will enable you to get an overview of a range of modern techniques and methodologies that underpin comtemporary biomolecular plant sciences.

A large part of your teaching will be delivered by academics from the University’s Centre for Plant Sciences (CPS) linked to the latest research in their areas of expertise. You’ll gain specialist training from these leading experts in the modern molecular aspects of plant science and its application to plant biotechnology.

You’ll study in a faculty ranked 6th in the UK for its research impact in the recent Research Excellence Framework (REF 2014).

Our extensive library of handy and helpful HSC Biology resources including past papers with worked solutions, study guides, study notes, essays written by students, assignments and many more, to help you prepare for the HSC

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&lsquothe study of life from the molecular level, through cells, tissues and organisms, to populations and ecosystems&rsquo

Whether students wish to progress to a career in a Biology related field or just to develop their skills and knowledge, The King&rsquos (The Cathedral) School Biology department offers something for everyone.

Through a variety of activities students are enabled to:

  • Recognise the impact of Biology on everyday life
  • Take informed decisions about issues that involve Biology
  • Develop Scientific skills
  • Acquire knowledge to build on

Staff are committed to making lessons in Biology as relevant and thought provoking as possible to students and so topical issues are included wherever possible giving students opportunities to engage in debate and develop their own opinions on very difficult issues.

In Years 7 and 8 Biology is taught as part of a balanced KS3 curriculum alongside Physics and Chemistry.

The biology topics covered at KS3 are as follows:

KS3 assessment includes formative Assessing Pupil Progress tasks (APP) and summative tests for each topic. Homework is set once every two weeks and should take no more than one hour.

KS3 science aims to develop the scientific skills our students require to embark upon their KS4 studies.

In Years 9, 10 and 11, pupils study KS4 Science. Science teachers will decide whether a student completes a Combined Science course or a Separate Science course. This decision is based upon work completed in KS3 and Year 9 Science lessons. Both courses are assessed solely in examinations, but both require that students complete a set of &lsquoRequired Practicals&rsquo during the course.

Combined Science (AQA 8464)

In this course, students study Biology, Chemistry and Physics. They are examined on all 3 of these disciplines and then awarded 2 GCSE grades.

  • Disease and Health
  • DNA and Inheritance
  • Evolution and Variation
  • Plants and Photosynthesis
  • Cell Division and Specialisation
  • Metabolism and Homeostasis
  • Hormones and Reproduction
  • Biotechnology and Uses of Living Organisms

Separate Science: Biology (AQA 8461)

In this course, students study all of the topics listed above but more detail is required for some of the topics. At the end of the course, they are examined and awarded a GCSE grade for Biology.

In Years 12 and 13 students follow the OCR Biology A GCE course. All units in the course are compulsory.

  • Module 2: Foundations in Biology
  • Module 3: Exchange and Transport
  • Module 4: Biodiversity, Evolution and Disease
  • Module 5: Communication, Homeostasis and Energy
  • Module 6: Genetics, Evolution and Ecosystems

Module 1: Development of Practical Skills in Biology is covered throughout both years.

The topics covered at KS5 give numerous opportunities for debate and students are encouraged to do further research on areas they are interested in.

Alongside the A-level in Biology, an additional accreditation called &lsquoPractical Endorsement&rsquo is awarded to students who demonstrate that they are competent practical scientists in a laboratory.

If students are interested in going onto a Biology related degree course or career, staff are always available for advice and discussion. KS5 students play an important role within the department, acting as role models for younger students and working as prefects who fulfil a range of roles including organising events for younger students.


The department is supported by a well-qualified technician and is well resourced so that many lessons have a practical component. At KS5 students are able to develop their Biotechnology skills through the use of bacterial transformation, PCR and gel electrophoresis.

Animal and organ dissections are used to demonstrate key parts of anatomy but are not a compulsory part of the course.

Regular Events

The Biology department runs events during National Science and Engineering Week to go beyond the curriculum and enhance students&rsquo experiences.

KS5 students take part in the Biology Olympiad each year.

Department Staff

Miss Faye Chantrell (FEC): Head of Biology Department
Mr Chris Dunn (CND): Teacher of Biology & Sixth Form Deputy
Mr Duncan Rhodes (DR): Teacher of Biology & Deputy Headteacher (Academic)
Mrs Julie Blakeley (JEB): Teacher of Biology
Dr Jane Combrink (XJC): Teacher of Biology
Mrs Debbie Wales (DW): Biology Technician

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School Website Design by e4education

Results and discussion

MATISSE was originally evaluated using the expression information of 1990 osmotic stress-associated genes in yeast and

69,000 yeast protein interactions. ICMg was tested with a slightly smaller set of osmotic stress-associated genes and using a different set of protein interaction data (see methods). MATISSE also adapted a strategy to generate connected modules by including information from genes that are not in the original selected gene set, referred to back nodes [12]. ICMg focused on the information within the set of selected genes only.

To compare and evaluate the performance of SSIM, we analyzed the same datasets used in MATISSE and ICMg studies (MATISSE dataset and ICMg dataset). Since MATISSE and ICMg used probabilistic approaches to optimize the construction of gene modules, the inferred connections and number of modules could vary in each run. To obtain the number of modules for comparison, MATISSE was executed 20 times as described [14], which yielded the median number of gene modules of 24 for both datasets. ICMg was then also executed 20 times with a fixed number of modules at 24. For SSIM, we adjusted the preference value to obtain the same number of modules (see methods).

Semantic similarity-integrated approach for modularization (SSIM) generates functionally relevant gene modules

GO enrichment analysis with statistical testing such as Fisher exact test was the most commonly used approach to evaluate the functional association of individual gene modules. A low p-value between a gene module and a GO term would imply a strong association of the module with the specific biological function represented by the term. Since SSIM integrates semantic similarity of GO BP (biological process) terms in gene module construction, it is expected to have a better GO enrichment performance compared to other methods. Therefore a different annotation scheme, MIPS FunCat [28], which is independent of GO, was also used to evaluate the functional associations of gene modules.

For a given significance level, the number of modules enriched with at least one annotation term and the number of annotation terms enriched in at least one module are referred as specificity and sensitivity [13]. For each method, the sensitivity and specificity were calculated and summarized into a measure of functional enrichment, an F-measure defined as F = 2 × Sensitivity × Specificity/(Sensitivity + Specificity) [13]. Note that the ratio of modules enriched with at least one annotation term (i.e. specificity) might be also expressed as precision. The results from SSIM showed better functional enrichment significance (F-measure) for MIPS FunCat annotations (as well as GO and GO BP terms) than other methods (Figure ​ (Figure1 1 and Additional File 1). ICMg gave comparable results to SSIM, whereas MATISSE showed lower performances in terms of both sensitivity and specificity. This could be due to a constraint on the size of the modules (a default parameter with no more than 100 genes per module was used in this study, but it is adjustable by user) and the addition of back nodes (genes that were not in the initial set of genes but were later included to make connected gene modules) in MATISSE.

Functional enrichment analysis results. The functional enrichment performance of each method was evaluated using three different annotation datasets, all GO terms, GO BP terms and MIPS FunCat terms. The results were summarised using F-measure (Y-axis, see text). Results for MATISSE and ICMg were obtained using the mean values of 20 runs.

To further evaluate the overall functional enrichment performance from the three different methods, semantic similarity between the terms and the shortest paths of the terms to the root (e.g. GO:0008150, biological process) were investigated (see methods). If enriched terms were closely related to each other (coherency) and were far away from the root in GO hierarchy (depth), they may reveal more specific and detailed biological functions. Enriched GO terms associated with the modules from SSIM have higher average semantic coherency, which measures how enriched GO terms are coherent in terms of semantic similarity, and comparable depth relative to other methods (see method and Additional file 2).

SSIM produces modules with strong functional association and high expression homogeneity

We also investigated the homogeneity of gene expression profiles and topological connectivity of modules generated by three different methods using average Pearson correlation as well as average clustering coefficient [29] of genes within the same module. As shown in Figure ​ Figure2, 2 , for both datasets, SSIM and MATISSE yielded modules with similar levels of expression homogeneity and topological connectivity while ICMg produced modules composed of densely connected genes with poorly co-expressed profiles.

Expression homogeneity and topological connectivity of modules. Expression homogeneity and topological connectivity of a module were calculated using average Pearson correlation among genes in the module and average clustering coefficient of the network generated by the genes, respectively. Average expression homogeneity and connectivity over all modules were shown for each method. For MATISSE and ICMg, mean and standard deviation over 20 runs were taken.

This finding also suggests the possibility of using SSIM as a tool to explore gene regulatory networks since genes with similar expression profiles are commonly co-regulated [4,7,30-33]. Notably, the study conducted by Ulitsky and Shamir [12] indicates that modules generated by random sampling of genes with sufficient network connectivity could give favorable topological properties and functional enrichment results, but with much lower expression homogeneity. This implies that significant GO enrichment results for gene modules might be obtained by chance if we just considered topological connectivity of genes thus, additional criteria such as gene expression homogeneity must be used to ensure the reliability of functional association for gene modules.

For a given number of modules, the SSIM approach seems to generate gene modules with better functional association and higher correlations in their expression homogeneity. For example, one of the ICMg modules (ICMg module 23) shared a large portion of genes with two modules generated by SSIM (SSIM module 4 and 10) (see methods and Additional File 3, Table S1). The GO terms enriched in the ICMg module 23 implicated two biological functions, "transport" and "lipid biosynthetic process" while in SSIM, the two functions were separated into two different modules, module 4 and 10, with much higher functional association (lower p-value) and expression homogeneity (Figure ​ (Figure3 3 and Additional file 3, Table S2 and S4).

Comparison between modules identified by ICMg and SSIM. One of the modules identified by ICMg method (ICMg module) shares a number of genes with two separate modules identified by SSIM (SSIM module A and B). Expression profiles of genes in three modules were shown on the left and protein-protein interaction network was shown in the middle. Genes shared by ICMg and SSIM modules are indicated by pink and light blue nodes, and ones exclusively belong to ICMg, SSIM module A and SSIM module B are depicted by white, red and blue nodes, respectively. In the right panel, enriched GO BP terms (p < 1 × 10 -5 ) and their uncorrected p-values for each module are summarized.

SSIM can be used to reveal the hierarchical structure of gene modules

To compare the efficiency of constructing gene modules with different algorithms, we have used a fixed number of modules (24 modules in this study). In SSIM, a larger preference value of affinity propagation [27] means that every gene is more likely to be an exemplar of a module (module center), which would produce a large number of modules composed of highly similar genes in terms of integrated similarity and allow us to view the system in detail. A smaller preference value would generate fewer modules which offer a broader, less detailed overview of the system. This implies that SSIM can also be used as a tool to generate a functional hierarchy of gene modules by virtue of using semantic similarity. As an example, we applied the SSIM approach to a MATISSE dataset with a wide range of preference values and chose three sets of modularization results with 12, 18 and 37 modules (see Additional file 4) to illustrate the hierarchical structure of gene module generated by SSIM. Figure ​ Figure4A 4A shows that large-size modules obtained from a smaller preference value were hierarchically decomposed into smaller modules using a larger preference value. As an example of the hierarchical structure of gene modules generated with SSIM using different preference values, one of the module obtained from the "12-module set" representing various "transport" functions is split into two groups, based on the membership of "18-module set", showing slightly different expression profiles. One of the two groups from the "18-module set" is further divided into two smaller groups based on "37-module set", which further stratify the "transport" function into protein and ion transport (Figure ​ (Figure4B 4B ).

Hierarchical structure of modules generated by SSIM approach. Using different preference values, three sets of modules (12, 18 and 37 modules) were obtained (see Additional file 4) and the membership of genes over the three module sets was expressed as a matrix form. When gene i and j belong to the same module and the membership is conserved in any one, two and three sets, the element of matrix in ith row and jth column is set to 1 (red, least conserved over the sets of modules), 2 (orange) and 3 (yellow, most conserved), respectively. If two genes are not in the same module, the corresponding element in the matrix has a zero value (black). Hierarchical clustering result of the matrix was shown in (A). Most orange and yellow squares are subsets of red squares along the diagonal, which means that a large module is hierarchically split into several smaller modules according to the change of preference values. (B) As an example, the decomposition of a large module (red square) identified in "12-module set" into smaller modules obtainable in "18-" and "37-module set" is shown with the expression profiles of genes and enriched GO BP terms. A module representing general transport function (12-module set) is stratified into modules specifically related to protein and iron ion transport (37-module set).

Extension of the module identified by SSIM approach

Suppose that we have information about a set of genes U and thereby choose a subset V as genes of interest to be used to construct gene modules. The remaining genes (V C ), where VV C = U and VV C = ø, are generally not considered in constructing gene modules. However, the genes in V C might have many interactions with the genes in gene set V and potentially provide important information in representing the biological function of the constructed modules. Such information can be incorporated by including these genes in V C using a module extension procedure (see methods). As an example, one of the modules identified by SSIM (using the MATISSE dataset) had 72 genes representing functions related to "cell cycle". The addition of 55 neighboring interconnected genes from V that were not in the initial gene list V C increased the significance level of enriched GO BP terms and the average clustering coefficient from 0.0648 to 0.2934 (see Additional File 5).

SSIM can be used to reveal biological processes involved in complex disease

The recently described gene networks involved in prion disease model was a significant development in the advance of systems biology [34]. It demonstrated the value of constructing gene networks to reveal biological processes involved in this complex disease. The study analyzed gene expression profiling results from several different experimental conditions and time points for prion disease animal model. A set of roughly 300 differentially expressed genes (DEGs) that were common to different experimental conditions (mouse strains and prion types) was identified from these analyses. These DEGs were first classified by GO annotations, then hand-curated and assigned into different gene networks based on functional enrichment results and prior knowledge of the genes. Additional non-differentially expressed genes were also included to complete and illustrate the functionality of the networks. It was surprising to find that the pathogenesis of prion disease can be largely explained by only four major networks: PrP Sc replication and accumulation, microglial and astrocytic activation, synaptic degeneration, and neuronal cell death [34]. Genes in these four networks are involved in proteolysis and lipid metabolism for PrP Sc replication and accumulation network, immune responses for microglial and astrocytic activation network, mitochondrial dysfunction and apoptosis for neuronal cell death network, and transcription-related function, intracellular signal transduction and ion transport-related function for synaptic degeneration network.

To test the feasibility of using SSIM in complex disease analysis, the same set of genes used in the prion network construction was fed into SSIM. A total of 16 gene modules were obtained and they could largely subsume into the four larger manually generated networks previously described (see Table ​ Table1 1 and Additional File 6). For example, modules 1 and 3 contain a total of 36 genes that are highly associated with lipid metabolism and proteolysis based on GO BP enrichment result, which almost completely recapitulate the key nodes involved in PrP Sc accumulation network. In addition to the modules related directly to the four reported networks, SSIM also suggested processes involved in tissue remodeling such as actin cytoskeleton organization (GO:0030036), angiogenesis (GO:0001525), multicellular organismal development (GO:0007275) and cell differentiation (GO:0030154) might also be involved in the progression of prion disease. We will conduct more detailed network analyses with SSIM using prion disease datasets including the comparison between different incubation times, host strains, and infectious agents, since this preliminary study agrees well with the manually constructed networks.

Table 1

Similarity between modules identified by SSIM and four major prion subnetworks

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