No wisdom in the crowd: genome annotation at the time of big data - current status and future prospects

Science and engineering rely on the accumulation and dissemination of knowledge to make discoveries and create new designs. Discovery-driven genome research rests on knowledge passed on via gene annotations. In response to the deluge of sequencing big data, standard annotation practice employs automated procedures that rely on majority rules. We argue this hinders progress through the generation and propagation of errors, leading investigators into blind alleys. More subtly, this inductive process discourages the discovery of novelty, which remains essential in biological research and reflects the nature of biology itself. Annotation systems, rather than being repositories of facts, should be tools that support multiple modes of inference. By combining deduction, induction and abduction, investigators can generate hypotheses when accurate knowledge is extracted from model databases. A key stance is to depart from ‘the sequence tells the structure tells the function’ fallacy, placing function first. We illustrate our approach with examples of critical or unexpected pathways, using MicroScope to demonstrate how tools can be implemented following the principles we advocate. We end with a challenge to the reader

THOUGHTS ON BUILDING AN ACADEMIC CAREER

We have many routes to success in agricultural economics: extension education, resident teaching, advising, research, and public service. In selecting problems to study we must be sensitive to needs of all our clientele. Several production economics concepts are relevant to allocating our own efforts. Noticing, recognizing, and experiencing surprise aid scientific discovery. We need to use heuristics, intuition, deduction, and induction, though consideration of science's ideal and real types shows that all these mental processes are fallible. We need special theories that have broad application. Replication deserves high priority. A few thoughts on the manuscript review process are presented.Teaching/Communication/Extension/Profession,

Closure Failure and Scientific Inquiry

Deduction is important to scientific inquiry because it can extend knowledge efficiently, bypassing the need to investigate everything directly. The existence of closure failure—where one knows the premises and that the premises imply the conclusion but nevertheless does not know the conclusion—is a problem because it threatens this usage. It means that we cannot trust deduction for gaining new knowledge unless we can identify such cases ahead of time so as to avoid them. For philosophically engineered examples we have “inner alarm bells” to detect closure failure, but in scientific investigation we would want to use deduction for extension of our knowledge to matters we don’t already know that we couldn’t know. Through a quantitative treatment of how fast probabilistic sensitivity is lost over steps of deduction, I identify a condition that guarantees that the growth of potential error will be gradual; thus, dramatic closure failure is avoided. Whether the condition is fulfilled is often obvious, but sometimes it requires substantive investigation. I illustrate that not only safe deduction but the discovery of dramatic closure failures can lead to scientific advances

A comparative survey of integrated learning systems

This paper presents the duction framework for unifying the three basic forms of inference - deduction, abduction, and induction - by specifying the possible relationships and influences among them in the context of integrated learning. Special assumptive forms of inference are defined that extend the use of these inference methods, and the properties of these forms are explored. A comparison to a related inference-based learning frame work is made. Finally several existing integrated learning programs are examined in the perspective of the duction framework

Automatic Deduction in Dynamic Geometry using Sage

We present a symbolic tool that provides robust algebraic methods to handle automatic deduction tasks for a dynamic geometry construction. The main prototype has been developed as two different worksheets for the open source computer algebra system Sage, corresponding to two different ways of coding a geometric construction. In one worksheet, diagrams constructed with the open source dynamic geometry system GeoGebra are accepted. In this worksheet, Groebner bases are used to either compute the equation of a geometric locus in the case of a locus construction or to determine the truth of a general geometric statement included in the GeoGebra construction as a boolean variable. In the second worksheet, locus constructions coded using the common file format for dynamic geometry developed by the Intergeo project are accepted for computation. The prototype and several examples are provided for testing. Moreover, a third Sage worksheet is presented in which a novel algorithm to eliminate extraneous parts in symbolically computed loci has been implemented. The algorithm, based on a recent work on the Groebner cover of parametric systems, identifies degenerate components and extraneous adherence points in loci, both natural byproducts of general polynomial algebraic methods. Detailed examples are discussed.Comment: In Proceedings THedu'11, arXiv:1202.453

The role of philosophical context in the development of research methodology and theory

The research strategy dictates the major direction of the research and constitutes one of the important decisions made by the researcher. However, researchers’ understanding on theory at the outset of the research guides the design of the research. The paper presents an overview of the involvement of theory within different research philosophies, approaches and methods. The relationship between data and theory is an issue that has been long debated. Moving from data to theory is commonly discussed in social constructionism with inductive approach and ideographic methods. However, within positivism philosophy with deductive approach and nomothetic methods, moving from theory to data is common. However, the growing concept of philosophical pluralism and methodological pluralism challenges the polarised views on philosophies and approaches, which suggests that methodologies are best used in complementary way. Keywords – Research Philosophy, Research Methods, Induction, Deduction, Theory, Pluralis

The role of philosophical context in the development of theory: Towards methodological pluralism

The research strategy dictates the major direction of the research and constitutes one of the important decisions made by the researcher. However, researchers’ understanding on theory at the outset of the research guides the design of the research. The paper presents an overview of the involvement of theory within different research philosophies, approaches and methods. The relationship between data and theory is an issue that has been long debated. Moving from data to theory is commonly discussed in social constructionism with inductive approach and ideographic methods. However, within positivism philosophy with deductive approach and nomothetic methods, moving from theory to data is common. However, the growing concept of philosophical pluralism and methodological pluralism challenges the polarised views on philosophies and approaches, which suggests that methodologies are best used in complementary way

What is abductive inference?

Abductive reasoning: constitutes according to Peirce the "first stage" of scientific inquiries (CP 6.469) and of any interpretive processes. "Abduction" is the process of adopting an explanatory hypothesis (CP 5.145) and covers two operations: the selection and the formation of plausible hypotheses. As process of finding premisses, it is the basis of interpretive reconstruction of causes and intentions, as well as of inventive construction of theories