Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

Traffic signals for lymphocyte recirculation and leukocyte emigration: The multistep paradigm

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

This invention provides methods of monitoring the expression levels of a multiplicity of genes. The methods involve hybridizing a nucleic acid sample to a high density array of oligonucleotide probes where the high density array contains oligonucleotide probes complementary to subsequences of target nucleic acids in the nucleic acid sample. In one embodiment, the method involves providing a pool of target nucleic acids comprising RNA transcripts of one or more target genes, or nucleic acids derived from the RNA transcripts, hybridizing said pool of nucleic acids to an array of oligonucleotide probes immobilized on surface, where the array comprising more than 100 different oligonucleotides and each different oligonucleotide is localized in a predetermined region of the surface, the density of the different oligonucleotides is greater than about 60 different oligonucleotides per 1 cm2, and the oligonucleotide probes are complementary to the RNA transcripts or nucleic acids derived from the RNA transcripts; and quantifying the hybridized nucleic acids in the array.

Expression monitoring by hybridization to high density oligonucleotide arrays

In the genome of a germ-line cell, the genetic information for an immunoglobulin polypeptide chain is contained in multiple gene segments scattered along a chromosome. During the development of bone marrow-derived lymphocytes, these gene segments are assembled by recombination which leads to the formation of a complete gene. In addition, mutations are somatically introduced at a high rate into the amino-terminal region. Both somatic recombination and mutation contribute greatly to an increase in the diversity of antibody synthesized by a single organism.

Somatic generation of antibody diversity

An immunoglobulin heavy chain variable region gene is generated from three segments of DNA: VH, D and JH

We studied the in vivo recombination between homologous DNA sequences cloned in phage lambda and a pBR322-derived plasmid by assaying for the formation of phage-plasmid cointegrates by a single (or an odd number of) reciprocal exchange. (1) Recombination proceeds by the RecBC pathway in wild-type cells and by low levels of a RecF-dependent pathway in recBC- cells. The RecE pathway appears not to generate phage-plasmid cointegrates. (2) Recombination is linearly dependent on the length of the homologous sequences. In both RecBC and RecF-dependent pathways there is a minimal length, called the minimal efficient processing segment (MEPS), below which recombination becomes inefficient. The length of MEPS is between 23-27 base pairs (bp) and between 44-90 bp for the RecBC- and RecF-dependent pathways, respectively. A model, based on overlapping MEPS, of the correlation of genetic length with physical length is presented. The bases for the different MEPS length of the two pathways are discussed in relationship to the enzymes specific to each pathway. (3) The RecBC and the RecF-dependent pathways are each very sensitive to substrate homology. In wild-type E. coli, reduction of homology from 100% to 90% decreases recombinant frequency over 40-fold. The homology dependence of the RecBC and RecF-dependent pathways are similar. This suggests that a component common to both, probably recA, is responsible for the recognition of homology.

https://www.genetics.org/content/genetics/112/3/441.full.pdf

Homologous Recombination in ESCHERICHIA COLI: Dependence on Substrate Length and Homology

We constructed full-length cDNA clones of Sindbis virus that can be transcribed in vitro by SP6 RNA polymerase to produce infectious genome-length transcripts. Viruses produced from in vitro transcripts are identical to Sindbis virus and show strain-specific phenotypes reflecting the source of RNA used for cDNA synthesis. The cDNA clones were used to confirm the mapping of the causal mutation of ts2 to the capsid protein. A general strategy for mapping Sindbis virus mutations is described and was used to identify two lethal mutations in an original full-length construct which did not produce infectious transcripts. An XbaI linker was inserted in the cDNA clone near the transcriptional start of the subgenomic mRNA; the resulting virus retains the XbaI recognition sequence, thus providing formal evidence that viruses are derived from in vitro transcripts of cDNA clones. The potential applications of the cDNA clones are discussed.

Production of infectious RNA transcripts from Sindbis virus cDNA clones: mapping of lethal mutations, rescue of a temperature-sensitive marker, and in vitro mutagenesis to generate defined mutants.

Sindbis virus, an enveloped virus with a single-stranded RNA genome, was engineered to express a bacterial protein, chloramphenicol acetyltransferase (CAT), in cultured insect, avian, and mammalian cells. The vectors were self-replicating and gene expression was efficient and rapid; up to 10(8) CAT polypeptides were produced per infected cell in 16 to 20 hours. CAT expression could be made temperature-sensitive by means of a derivative that incorporated a temperature-sensitive mutation in viral RNA synthesis. Vector genomic RNAs were packaged into infectious particles when Sindbis helper virus was used to supply virion structural proteins. The vector RNAs were stable to at least seven cycles of infection. The expression of CAT increased about 10(3)-fold, despite a 10(15)-fold dilution during the passaging. Sindbis virus vectors should prove useful for expressing large quantities of gene products in a variety of animal cells.

https://science.sciencemag.org/content/sci/243/4895/1188.full.pdf

Henry V. Huang

Papers

An immunoglobulin heavy chain variable region gene is generated from three segments of DNA: VH, D and JH

Homologous Recombination in ESCHERICHIA COLI: Dependence on Substrate Length and Homology

Production of infectious RNA transcripts from Sindbis virus cDNA clones: mapping of lethal mutations, rescue of a temperature-sensitive marker, and in vitro mutagenesis to generate defined mutants.

Sindbis virus: an efficient, broad host range vector for gene expression in animal cells.

A single VH gene segment encodes the immune response to phosphorylcholine: Somatic mutation is correlated with the class of the antibody