Lecture 1
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This document provides an introduction to bioinformatics, beginning with basic biological concepts like cells, DNA, genes, and genomes. It then discusses the history of bioinformatics, from early biological research to the completion of the Human Genome Project. Finally, it outlines several present and future areas of research in bioinformatics, including sequence alignment, genome assembly, gene expression analysis, and systems biology. The overall document serves as a high-level overview of key topics and concepts relevant to understanding bioinformatics.
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-- What is DNA?
-- What is mitochondrial DNA?
-- What is a gene?
-- What is a chromosome?
-- How many chromosomes do people have?
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-- What is genetic mapping?
-- How do researchers create a genetic map?
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this is done by me and my team mates of Wayamba University Sri Lanka for our project.From now we decided to allow download this file.I would be greatful if you could send your comments..
And I'm willing to help you in similar works.I'm in final year of my degree(.BSc Biotechnology)..
pubudu_gokarella@yahoo.com
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Genomics is the study of genomes, including the structures and functions of genomes. A genome is an organism's complete set of DNA and includes all of its genes. Genome sequencing projects map and sequence the entire DNA of different species to understand their genes. Important genome sequencing projects have included microorganisms, plants, insects, and humans. The Human Genome Project aimed to map and sequence the 3 billion base pairs in human DNA to identify all human genes.
Sk microfluidics and lab on-a-chip-ch3
This document provides an overview of molecular biology concepts and analytical tools relevant to lab-on-a-chip applications in medical diagnostics. It describes the basic biological units of cells and DNA, as well as DNA analysis techniques like genome projects, DNA sequencing, and measuring gene expression using microarrays. Specific concepts covered include the central dogma of biology, DNA/RNA structure, genes and chromosomes, and how proteomics and single molecule DNA manipulation can be used for medical analysis.
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Current Trends in Molecular Biology and Biotechnology
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Lecture 7
1. Hidden Markov Models (HMMs) are used to model problems where the true underlying state is hidden, but outcomes are visible.
2. An example of an HMM is the occasionally dishonest casino problem, where a die can be either fair or loaded, but the actual die state is hidden and only the outcomes are observed.
3. The Forward Algorithm and Viterbi Algorithm can be used to calculate the probability of state sequence combinations that could have generated an observed outcome sequence, and find the single most likely state sequence, respectively.
Lecture 8
This document discusses maximum likelihood estimation for phylogenetic trees. It provides the key inputs needed for calculating maximum likelihood: 1) the tree topology with branch lengths, 2) the substitution rate matrix, and 3) the stationary probabilities. It also provides an example calculation, explaining how to handle branches where the sequence changes over time, requiring calculation of separate branch lengths before and after the change point. The maximum likelihood is computed by multiplying the stationary probability, substitution rate, and branch length along each branch in the tree.
Lecture 6
The document summarizes the process of performing a database search using the FASTA algorithm. It discusses true positives, true negatives, false positives, and false negatives in database searches. It then explains how to calculate selectivity and sensitivity for a search. Finally, it outlines the steps to build hash tables and offset tables to perform alignment between a query sequence and target sequence using the FASTA algorithm. The key steps are hashing the query sequence, building target tables, extending the target table based on the hash table, constructing an offset table from matches, and updating the starting position of the target sequence based on the maximum offset.
Lecture 2
This document provides an overview of molecular and cellular biology concepts including:
- The structures and differences between eukaryotic and prokaryotic cells.
- The processes of mitosis and meiosis.
- The structures of DNA and RNA as well as DNA replication.
- The central dogma of biology explaining how DNA is transcribed into mRNA and then translated into protein.
- Additional concepts like gene regulation, alternative splicing, and different biological terms.
Lecture 5
The document discusses several topics related to gene duplication and read mapping. It first defines gene duplication as the duplication of a region of DNA containing a gene. It then discusses homologs, orthologs, and paralogs that result from gene duplication and speciation. The document next describes read mapping as aligning short DNA reads to a reference genome. It explains several data structures used for genome indexing in read mapping, including keyword trees, suffix trees, suffix arrays, and the Burrows-Wheeler transform.
Lecture 4
This document provides an overview of sequence alignment methods. It discusses pairwise sequence alignment, including global alignment using Needleman-Wunsch and local alignment using Smith-Waterman. It also covers multiple sequence alignment, comparing progressive and iterative methods. Challenges with multiple sequence alignment are noted, such as computational expense and difficulty in scoring and placing gaps for distant sequences.
Lecture 3
This document discusses DNA sequencing techniques. It begins by defining DNA sequencing as determining the order of nucleotides in a DNA molecule. It then summarizes 4 generations of sequencing methods: 1) Sanger sequencing from 1977, the predominant early method; 2) Next generation techniques from 2005-2007 including 454, SOLiD, and Illumina that enabled high-throughput short reads; 3) Third generation methods like PacBio and Oxford Nanopore that enable long reads but with lower accuracy; and 4) Some additional terms used in sequencing like oligonucleotides, plasmids, and cloning vectors.
ABOUT ME!
Owali Ullah Shawon is a student at the Department of Computer Science and Engineering. He received high marks in SSC and HSC exams and currently has a 3.69 CGPA pursuing his B.Sc. from Daffodil International University. He comes from a family with his late father, housewife mother, brother who is a businessman, and sister who is also a student. His goals are to complete his B.Sc. in CSE with high marks, start a business, expand into more industries, open a medical school and do social work, and ultimately become a leader rather than a boss.
Electrical Circuit
The document describes two laws developed by Gustav Kirchhoff in 1845 that became central to electrical engineering. The laws were generalized from the work of Georg Ohm and can also be derived from Maxwell's equations. Kirchhoff's voltage law (KVL) and Kirchhoff's current law (KCL) state that the sum of voltages in a closed loop is zero and that the algebraic sum of currents entering or leaving a node is zero, respectively. These laws form the basis for circuit analysis techniques like node analysis and mesh analysis.
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This document discusses stacks, which are a useful data structure in programming. Stacks follow the LIFO (Last In First Out) principle, where new items are added to the top of the stack and removed from the top. The document provides code to implement a stack using a linked list in C, including functions to push, pop, and display items in the stack. It contains a sample main program that uses a menu to allow the user to push, pop, or display the stack.
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Nucleophilic addition is the most important reaction of carbonyls. Not just aldehydes and ketones, but also carboxylic acid derivatives in general.
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Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
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In this presentation include the prototype drug SAR on thus or with their examples .
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原版制作(carleton毕业证书)卡尔顿大学毕业证硕士文凭原版一模一样
原版纸张【微信：741003700 】【(carleton毕业证书)卡尔顿大学毕业证】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
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Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
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Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
Deep Software Variability and Frictionless Reproducibility
Deep Software Variability and Frictionless ReproducibilityUniversity of Rennes, INSA Rennes, Inria/IRISA, CNRS
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
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When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
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Lecture 1
- 1. INTRODUCTION TO BIOINFORMATICS Lecture – 1 Nafis Neehal, Lecturer, Department of CSE, DIU
- 2. CONTENTS 1. Basics - Cell - Nucleus - Chromosome - DNA - RNA - Gene - Genome 2. Brief History 3. Present and Future Scopes
- 3. 1. Begin With Basics Let’s start with the very basics and learn step by step, TOGETHER!
- 4. CELL ▹Cell Types – • Prokaryote – no nucleus or membrane-bounded organelles. Ex- Bacteria • Eukaryote – have nucleus and other membrane- bounded organelles. Ex- Human ▹Cell Contents - • Mitochondria – Power House of Cell • Lysosomes – Holds enzymes created by a cell • Golgi Apparatus (body) – Processes protein and lipids • Endoplasmic Reticulum – Involved in protein and lipid synthesis • Nucleus – Brain of the cell • Cytoplasm – liquid inside cell where organelles float
- 5. NUCLEUS • Nuclear membrane – 2 layered membrane • Nucleolus – dense object inside nucleus • Chromatin – Packed inside the nucleus of every human cell is nearly 6 feet of DNA, which is divided into 46 individual molecules, one for each chromosome and each about 1.5 inches long. 23 pairs of chromosome, 22 pairs of common autosome, 1 pair sex chromosome • Nucleoplasm – dense liquid inside nucleus
- 6. Chromosome
- 7. NUCLEIC ACID (DNA & RNA)
- 8. GENE • A gene is the basic physical and functional unit of heredity. • Portion of DNA which acts as instruction to make proteins. • Human gene can have few hundred to 2 million base pairs. • The Human Genome Project has estimated that humans have between 20,000 and 25,000 genes. • Every person has two copies of each gene, one inherited from each parent. • Most genes are the same in all people, but a small number of genes (less than 1 percent of the total) are slightly different between people (called allele). • These small differences contribute to each person’s unique physical features.
- 9. GENOME • A genome is an organism’s complete set of DNA, including all of its genes. • Each genome contains all of the information needed to build and maintain that organism. • In humans, a copy of the entire genome—more than 3 billion DNA base pairs—is contained in all cells that have a nucleus.
- 10. 2. HISTORY A Journey from Biology to Bioinformatics
- 11. WHAT IS BIOINFORMATICS? ▹The applications of computer sciences to molecular biology in particular to the study of macromolecules such as proteins and nucleic acids. ▹Bringing biological themes to computers
- 12. ” SYNONYMS Molecular Bioinformatics, Computational Biology, Biocomputing
- 13. FROM BIOLOGY TO BIOINFORMATICS ▹From Academic Interest to Commercial Interest ▹From Knowledge Discovery to Industrial Development ▹Added Pursuit for Longer Life and Cure for Diseases ▹Tremendous recent progress in Biology and Engineering
- 14. ▹ Completed between 1986 to April 2003 ▹ Identify all genes of Human DNA ▹ Around 3 Billion Nucleutide Bases (A, T, G, C) in a human body ▹ Average gene consists 3000 bases, varies in size (Largest Gene – 2.4 Million Bases) ▹ Total Number of Genes around 30,000 ▹ Functions are unknown of almost 50% discovered genes HUMAN GENOME PROJECT
- 15. 3. BIOINFORMATICS – PRESENT & FUTURE SCOPES What’s happening now and what might happen in the upcoming years?
- 16. SCOPE OF RESEARCH Sequence Alignment Arranging DNA/RNA/Protein Sequences to identify regions of similarity. Genome Assembly Merging long/short reads by aligning and produce original ancestral gene. Read Mapping Mapping generated long/short reads to a reference sequence. Evolution Phylogenetics Studying evolutionary relationships among bilogical entities. Statistical Phylogenetics Performing statistical analysis for finding evolutionary relationships between biological entities. Population Genetics Study of genetic variation within populations.
- 17. SCOPE OF RESEARCH (CONT.) Genome Annotation Process of identifying location of genes and all other coding regions in a genome. Gene Expression Analysis Gene expression analysis is the process by which information from a gene is used in the synthesis of a functional gene product. Computer Aided Drug (CAD) Design Designing new medications with knowledge of a biological target and with help of computer tools. Structure Prediction (RNA, Protein) Predicting 3D structures of RNA and Protein. Association Mapping Linkage Analysis and disequilibrium mapping. Basically links phenotypes with genotypes. Systems Biology Study of systems of biological components.
- 19. 70 Miles per Hour Nerve Impulses run to and from Brain 20% Oxygen Brain uses 20% of Oxygen entered into the blood 5x Times Brain’s storage capacity compared to Encyclopedia Britannica 80% Water Human brain has 80% water
- 20. CURIOUS?
- 21. ▹ Cell Structure - https://www.youtube.com/watch?v=URUJD5NEXC8 Youtube Links