How difficult is it for one with a B.S. in Applied Physics

[dimensionless]

How difficult is it for one with a B.S. in Applied Physics to get into this field? How about if one also knows a little bit about Unix and programming?

 

[cronxeh]

Apply for a masters degree but keep in mind you will need those undergrad courses as prerequisites:

General Physics 1+2, General Chemistry 1+2, Organic Chemistry 1+2, Multivar Calculus, Probability/Statistics, Complex Variables, Data structures, Object oriented C++, Discrete mathematics, DiffEQ, Linear algebra

Here are some courses from a university curriculum for Bioinformatics:

Chemical Foundation for Bioinformatics
An intensive review of those aspects of Organic Chemistry and Biochemistry necessary to begin research in Bioinformatics and to enter graduate courses in Biology. Covalent bonding, quantum mechanical basis of bond formation, three-dimensional structure of molecules, reaction mechanisms, catalysis, polymers, enzymes, thermodynamic and kinetic foundations, metabolic pathways, sequence and structure of macromolecules. This course will make extensive use of computer approaches to convey the essential computational and visual nature of material to be covered.

Biological Foundation for Bioinformatics
An intensive review of those aspects of Biochemistry, Molecular Biology and Cell Biology necessary to begin research in Bioinformatics and to enter graduate courses in Biology. The areas covered will include cell structure, intracellular sorting, cellular signaling (i.e. receptors), Cytoskelton, cell cycle, DNA replication, transcription, translation. This course will make extensive use of computer approaches to convey the essential computational and visual nature of the material to be covered.

Chemoinformatics
Review of Database Theory, Chemical Structure Representation; connection tables, line notations, structure diagrams, Representations of Chemical Reactions, Structure manipulation: Graph Theory, Structure Analysis: ring perception, structural fingerprints, symmetry perception, Molecular Modeling Algorithms, Genetic Algorithms, Simulated Annealing, QSAR historical approaches, Structural Search of Chemical Databases, Commercial Chemical Information Databases, Combinatorial Chemistry and diversity assessment.

Bioinformatics I: Sequence Analysis
Computer representations of nucleic acid and protein sequences, pairwise and multiple alignment methods, available databases of nucleic acid and protein sequences, database search methods, scoring functions for assessment of alignments, nucleic acid to protein sequence translation and codon usage, genomic organization and gene structure in prokaryotes and eukaryotes, introns and exons, prediction of open reading frames, alternative splicing, existing databases of mRNA, DNA, Protein, and genomic information. An overview of available programs and of resources on the web.

Bioinformatics II: Protein Structure
Available online in future semesters
Protein folding representations, databases of protein folding classes, secondary structure prediction, tertiary structure prediction via computer folding experiments threading, and homology model building, prediction of post translation modification sites, active and binding sites in proteins, representations of contiguous and non-contiguous epitopes on protein surfaces at the sequence level, representations of functional motifs at the three dimensional an at the sequence level.

Bioinformatics III: Functional Prediction
Available online in future semesters
Functional classifications of proteins, prediction of function from sequence and structure, Orthologs and paralogs, representations of biological pathways, available systems for the analysis of whole genomes and for human-assisted and automatic functional prediction.


And the optional electives (recommended):

Liquid Chromatography
A variety of separation modes using different combinations of stationary phase and mobile phase are being used in liquid chromatography. This course will illuminate the separation mechanism in each of these modes. Starting with fundamentals of liquid chromatography, we will learn about column packing materials, partitioning in different modes of chromatography, preparative separation, and method development including gradient elution.

Chemistry of Colloids
Colloidal dispersions are heavily being used in today's society from paints and inks to drug delivery systems. This special topics course will cover various topics of colloids ranging from preparation of colloids and characterization methods to thermodynamics. Both aqueous and non-aqueous dispersions will be considered.

Oh and to answer your original question: BS in Applied Physics is practically useless in Bioinformatics

 

[Physics Monkey]

I don't know if I would agree that a B.S. in Applied Physics is totally useless for studying bioinformatics. It depends somewhat on the nature of your applied physics degree, perhaps you could supply some details? In the mean time, you will find that a solid grounding in quantum mechanics, electromagnetism, thermodynamics, and especially statistical mechanics really constitutes a very good base upon which to build a knowledge of bioinformatics. In addition, the analytical skills you have developed as an undergraduate physics major are invaluable, and I personally find that this alone almost justifies a physics degree no matter what field you want to go into. You will definitely have a lot of biology to catch up on and strong programming skills are a must. However, in my opinion a good B.S. in physics is actually a great way to start advanced degrees in bioinformatics, biophysics, etc. Just my thoughts on the matter, and bear in mind that we may be speaking about very different kinds of programs.

 

[cronxeh]

I don't know if I would agree that a B.S. in Applied Physics is totally useless for studying bioinformatics. It depends somewhat on the nature of your applied physics degree, perhaps you could supply some details? In the mean time, you will find that a solid grounding in quantum mechanics, electromagnetism, thermodynamics, and especially statistical mechanics really constitutes a very good base upon which to build a knowledge of bioinformatics. In addition, the analytical skills you have developed as an undergraduate physics major are invaluable, and I personally find that this alone almost justifies a physics degree no matter what field you want to go into. You will definitely have a lot of biology to catch up on and strong programming skills are a must. However, in my opinion a good B.S. in physics is actually a great way to start advanced degrees in bioinformatics, biophysics, etc. Just my thoughts on the matter, and bear in mind that we may be speaking about very different kinds of programs.

I was under the impression he meant 'to get into' as in start working as a bioinformaticist - which would render him incompetent with a BS in Applied Physics for that particular field. To study Bioinformatics on a graduate level, BS in Applied Physics is a very good background